Conversational Analysis of Chat Room Talk PHD thesis by Dr. Terrell Neuage University of South Australia National Library of Australia.

THESIShome ~ Abstract.html/pdf ~ Glossary.html/pdf ~ Introduction.html/pdf ~ methodology.html/pdf ~ literature review.html/pdf ~ Case Study 1.html/pdf~ 2.html/pdf~ 3.html/pdf~ 4.html/pdf~ 5.html/pdf~ 6.html/pdf~ 7.html/pdf~ discussion.html/pdf ~ conclusion.html~ postscipt.html/pdf~ O*D*A*M.html/pdf~ Bibliography.html/pdf~ 911~ thesis-complete.htm/~ Terrell Neuage Home Appendixes 1, 2, 3, 4, 5, 6, 7. DATA ~ Case Study 1 ~ 2 ~ 3 ~ 4 ~ 5 ~ 6 ~ 7 ~ These links are from early notes and not the final edits which are in the published version available at the University of South Australia only. Not all links are active due to changing domains. Home page see http://neuage.co / http://neuage.us

Terrell Neuage Conversational analysis of chatroom talk - thesis

Wednesday, October 29, 2003 4:06 PM

Methodology. 1

3.1 Introduction. 1

Qualitative research. 2

Research techniques. 6

Ethnographic approach. 8

Conversation Analysis. 17

3.2 Theoretical Framework. 21

3.2.1 Assumptions. 22

3.3 Protocol of a transcription methodology. 29

3.4 Data collection. 38

3.5 Ethical issues. 45

Wednesday, October 29, 2003 2:47 PM 15,179 words

Methodology

3.1 Introduction

From a conventional perspective, referring to the data samples in this study in terms of “conversation” is a misnomer, as what is currently considered conversation has a history as an interchange through speech: an act requiring physical proximity to permit audibility – and an act therefore precluding written text. In this section I will describe the theories that I will use to establish an interpretation of conversation for use in this study of online, texted ”chat”. Chatroom ”talk” in this study is analysed in accordance with the general requirements of conversation analysis, i.e. turn- taking, sequential organisation, repair organisation and turn construction design. Other researchers have found conversation analysis to be a good tool for studying CMC (see for instance Dingley, 2000; Titscher, Meyer, Wodak, and Vetter, 2000; Garcia and Jacobs, 1999).

From the outset it is clear in all CMC studies that methodology in cyberspace is different from that used in studies conducted in any other environment. Sherry Turkle writes for instance in relation to her own ethnographic work into online communication:

Virtual reality poses a new methodological challenge for the researcher (Turkle, 1995, p.34, quoted by Hamman, 1966)

The communicative relation online – including that for researchers – changes in both predictable and unpredictable ways. Some of these we may still be unable to determine, leaving much uncaptured for analysis by current techniques. Online “conversation” falls partially inside, and partially outside, the specialized repertoires of conventional linguistic and social research. Not only then does any attempt to examine its already observably rich repertoires of communicative practice demand a hybridized appropriative methodological practice, but even then it seems likely that many aspects will remain obscured. What is evident though is that whatever strategies are adopted (or adapted), these must optimize a critical and reflexive practice: one which can critique the potential of whichever techniques are utilized, within the inquiry act itself. The dilemma thus appears to demand a qualitative, or even post-qualitative-experimental approach.

Qualitative research

Not only does the researcher-research subject relation change online, but problems of validity and verification of results occur, since it is impossible to guarantee either participant identity or ongoing site-access for replication. Criteria developed by Guba and Lincoln (2000) focus on truth, value-credibility, auditability, fittingness and neutrality-conformability within qualitative research. Over the past two decades qualitative social inquiry has developed both approaches and instruments for assessing the validity of its techniques. Methodological rigor in online qualitative research is however difficult to carry on, not least due to its recency. Given the diversity of the online activities under question; the widespread debate over and suspicion of the authenticity behind online communicative acts, and the lack of consensus about rules to which online behaviours should conform, the research object itself appears notably unstable. Meanwhile, the fast feedback loops of CMC informational flows mean that quantitative research is an inherent dimension of online usage – so that the territory is enmeshed within methodological practices contested within qualitative work. Why then attempt to conduct such research, given such a seemingly intractable research object?

To some extent the broad field of qualitative research methodology has of itself resolved these issues. The view that there is in fact nothing special about qualitative research, and that it should be evaluated by the same criteria as quantitative studies, with mechanisms for validity, reliability and generalisability (Jasper, 1994; Cavanagh, 1997; Appleton, 1995[1]) has become commonplace. Yet this newly developed confidence changes with cyber-ethnology, due to the constancy of advances in CMC technology. While it is perfectly possible to propose application of a research design arising in now quite conventional models of qualitative social inquiry, drawing for instance on established methods used in socio-linguistic or communications research, online communications presents unprecedented instabilities and insecurities, even at the most basic levels of observation or data collection. For example for this study I have ‘captured’ conversation from chatrooms by cutting and pasting the chat turn-takings, to archive a secure and revisitable data corpus of chat. But in the java script chatrooms rapidly coming to dominate the mode, the only way to save the chat texts is either by writing down the chat – which is difficult if the chat is scrolling by at a rapid rate – or by taking a screen-shot of the chatroom, which would show only a few lines of chat captured at a particular time. While it is possible to design and provide text-saving chat services, technical designers presumably do not consider the act of research collection a sufficiently dominant demand to provide such a function. Instead, chat, like its off-line social equivalent, is treated as an ephemeral and perhaps trivial activity, not worth preserving. The rapid scrolling of speed-entered postings; the de-structured sentences and incomplete spelling; the crunching into abbreviations and semi-graphic compounds, and the mixing of unrelated “threads”, all signal a scrambled and ill-valued communicative form, operating at a basic and seemingly underdeveloped level. And yet the demand for space in these new facilities simultaneously signals them as of significance for increasing numbers of online participants. And while quantitative research can, and does, provide statistical evidence in support of this observation, it cannot inquire into why chat has evolved so rapidly, and is in such demand. Nor can it observe or categorise the online behaviours developing inside the new communications space. Qualitative research, with its observational-descriptive foundation and its subsequent analysis calling on increasingly rich repertoires of socio-cultural explanation, offers a much greater chance of both recording and explaining what is going on in online chat, and why.

Qualitative research, using multiple methodologies, is at core about the behaviours of people studied in their own social settings and understood in terms of the meanings those people themselves bring to their situation (Lincoln and Denzin 1994, p. 2). Chatrooms are ‘momentary’ social settings created not to last further than the immediate ‘talk’. Pursuit of these online participants beyond these fleeting moments of their talk is difficult. Qualitative research however, arising primarily within the broad field of social sciences, has more recently allied itself to the critical textual techniques of inquiry typical of the new humanities. Turner (1993: 205-219) outlines the development of this dual focus within varying traditions of the study of communications media.

In the US for many years, the study of the mass media occurred in the behavioural sciences, while in Europe it was the domain of the humanities, particularly English, and of certain approaches to sociology. Further exacerbating the debate between the paradigms, though, was an essentially political dispute between the liberal-democratic US tradition and the Marxist European tradition (p. 208).

While acknowledging the ongoing usefulness of the semi-quantitative empirical methodologies on which US media study was based (in particular, the power of Content Analysis to locate powerfully repeating narrative structures and selective representations), Turner sees the textual turn as supplying some key deficiencies in the ongoing analysis of communications media.

The idea of the text, then, corrects precisely the flaw in empirical or social sciences-based communication theory and its dealing with ‘the message’: it problematises the ways meanings are generated. It interests itself in the various textual forms employed (television genres for instance), and it privileges the reader-text relationship over the sender-receiver relationship (p. 219).

For Turner, this renewed and re-theorised communication studies, by adopting the stances outlined in European structuralist philosophy, opened a whole new set of “close reading” analytics for media forms, and re-oriented understandings of what mediated communications activities enacted, socially and culturally.

A couple of key moves made within the various streams of structuralism are relevant to the methodologies we are dealing with here. Firstly, there is the work within structural linguistics which reorients the study of language so that it is understood as a system of relationships rather than a system of nomenclature. Understood in such a way, language does not describe reality, it actually constitutes it. Our language system determines, delimits and shapes the way we understand the world. Therefore, to examine the structures of our language is to examine the structures of culture in general (p. 219).

Extending outwards from the linguistic structuralism of de Saussure and the theorization of the US semiotician C S Peirce, a generalized semiotics allowed for the examination of the multi-formatted communication systems of the modern world: speech, text, audio, graphics, each contributing to the acculturative processing of the various selves and social sectors and pre-dispositions within the relatively loose social formations operating after the “de-legitimation” of social institutions from the mid-twentieth century onwards (Castells, 1997). Returning to the inquiry paradigms proposed by Guba and Lincoln (1994), we can see that social science has in itself followed a similar trajectory of transformation, moving from the relative certainties of positivism, to a more open and reflexive set of methods under postpositivism, a re-examination of the social embeddedness of social inquiry itself with the introduction of critical theory, and finally an assimilation to the structuralist and post-structuralist positions on the constitutive role of knowledges, as expressed and exchanged – communicated - through language and texts. With this arrival at what social sciences terms constructivism, the inquiry paradigm stresses not which meanings are present, but how they are formed, and what their presence signals about the society and community of users from which they arise, and to which they return significance. Following this lead much qualitative research NEW SITE = JULY 2014 - http://neuage.us/2014/July/ - Today is construed as interpretive inquiry within a constructivist paradigm.

Research techniques

Such a position legitimates analysis of the new texting-enterprises of CMC – but it also anticipates that these too will have powers of social and cultural formation. With the growing attention paid to CMC and to the Internet, as well as to other technologies of instant communication such as mobile phones (cell phones) and hand-held devices, establishing ways to analyze text-based ‘talk’ will involve multiple methodologies, as discussed in the previous literature review chapter – yet in all cases, with an emphasis on the social constructivist role of those repeating tendencies uncovered through the text-analytic techniques. In this study I am using a different analytical approach in each case study of a particular chat community, to examine what works with describing online talk, at the same time as I outline those varying forms of online talk already evident from site to site. Using one approach for communication processes as complicated as chatroom ”talk” is not sufficient. Nor is there yet in evidence any strong disposition towards a particular or preferred method for online communication analysis. Scholars from various traditions have contributed to early examinations of online communication, without dictating or even privileging any one technique. This study thus proposes not just a mixed set of approaches, but intends to problematise the entire issue, testing the strengths of a range of existing language and text based methods, against a selection of different CMC styles of online ‘chat”. In some cases, the analysis will move in close to the talk techniques, annexing for instance Conversational Analysis in the Sacksian ethnomethodological tradition, to capture how speech exchange is regulated online, and to assess whether this new “technologisation” of talk relations alters the regulatory practices and systems established within real-world or physically present speech. I similarly use Discourse analysis in Case Study Five to examine the message structures organizing an online community into consensual and resistant or negotiative communicative moments. How chat is organized, how it is used and how is it understood are each newly problematic when the social and possibly cultural contexts are stripped away, along with the negation of physical proximity and accompanying cultural cues. How are we able to string words together to make meanings acceptable to a given online chat community? How far do such communities display specialist chat repertoires of language selection and use – and how do these relate to offline usage?

Discourse Analysis is the analysis of language beyond the utterance: the meaning systems annexed in a given set of utterances, which in their turn work “constitutively” to transform or reinforce meaning systems. Since the capacity to enter an online ‘site’ is so ”unnaturally” heavy in its reliance on linguistic cues, this study must anticipate the display of certain language behaviours and practices co-extensive with those operating offline – perhaps generally, within a language group, and perhaps specifically, demarking select or specialist communities within a language group. Yet, in spite of the relative recency of the evolution of online chat and its communicative relatives (SMSing for instance), there is also strong evidence for an emergent yet already rich set of online language behaviours – and this too must be examined, often in the absence of any descriptive categories from within linguistic analysis. Owing to chatrooms having a strong emphasis on special communicative forms such as abbreviations and emoticons, one of my case studies (Case Study Three) uses semiotics to examine online communication. Its potential to cross-communicative formats: to analysis within the same repertoire images, words and mixed-mode forms, such as conventions of abbreviation, allows a more thorough study of this emergent communicative format.

Beyond such attempts to capture new and hybrid communicative formats for examination, lies the need to find analytic techniques to assess what such formats are enacting, and why online users have moved to them. I use both semantics and pragmatics to study the meaning of the language of chatters, each oriented to a different aspect of the formation of meaning. Pragmatics is more concerned with what people intend to communicate in real life situations than semantics, which is concerned with what language selections (online, abbreviations, emoticons, usernames, icons) “mean” in isolation from its social context, and in relation to its positioning within an overall language system. Semantics and pragmatics are concerned with two types of questions; respectively: Semantics: What does X mean? and Pragmatics: What did you mean by X? (Leech, 1983:6). Speech Act Theory (Case Study Four) examines the practical use of language to achieve a goal, and so extends the study into how chat participants online direct their communicative activities towards social actions – whether in the online or offline ‘world’. A speech act is a basic unit of language not just used to designate something; it actually does something – and the recognition that language in the ‘virtual’ world of the chatsite enacts outcomes just as it does in the physical world, is central to a study which ranges as far as Discourse Analysis, and which is founded in constructivist social inquiry. Overall therefore, this study will be arguing for a wide-ranging and mixed methodology in its examination of seemingly trivial ‘chat’ activities, hoping to reveal both some of the complexities of online communication, and the potential of existing linguistic techniques, in combination, as a means of explaining the attractions of chat. Finding commonality in conversational practices and ways of analyzing them, along with differences, is a way of establishing an online discourse analysis method (ODAM) – simultaneously recognizing the challenges of such a task:

Multiple methods give a fuller picture and address many different aspects of phenomena, however multiple sources of data demands multiple data analysis skills (Silverman, 2000, p.50).

In sum, this study is embedded not within any one specialist tradition of language-based research, but seeks instead a general overview of chat usage, deploying more focused linguistic-based techniques to approach specific issues, within specific sites. Overall, it remains an ethnographic study, collecting, observing and reporting on the specific social and cultural practices of a specified population: online chat participants.

Ethnographic approach

My proposal creates specific theoretical and methodological "focus points" within this multidisciplinary study, and establishes a new direction for study of online communicative practices.

I have taken an ethnographic approach to researching text-based chatrooms as it provides a method for learning about, and learning how to talk about, chatroom cultures, by placing the researcher in the research. I am inevitably part of the research I am investigating, as I need to enter a chatroom in order to ‘capture’ the dialogue[2]. Most research conducted online uses ethnography as a methodology (see Hamman, 1996, 1998, 1999). Ethnography at its simplest is just writing about cultures. Online cultures are discussed throughout this thesis (see Hamman, 1996, 1998, 1999; Rheingold, 1991, 1993, 1994; Stubbs, 1996, 1998; Cyberrdewd, 1999; and Turkle, 1995, 1996). Ethnography is one of the approaches within anthropology that emerged in the late nineteenth century (for histories, see Stocking 1968, 1983). A linguistic observer in a cyber-ethnography field studies the chatroom as a cultural field, makes records, and interprets some aspects of the taken for granted culture of the people in the chatroom.

There is however ongoing debate within ethnography over the relationship of the researcher to the research object, and especially to the research subjects, given the researchers presence within the data field, and the problem of their influence on that field (see Schaap, 2001; Hammersley and Atkinson, 1995; Seiter, Borchers, and Kreutzner, 1989; Moermanand and Sacks, 1988 and Hymes, 1974). To capture chatroom data, I had to be present myself. So I became a participant in each cited chatroom, albeit mostly a silent one. A direct response was made to my presence in only one chatroom. There may have been indirect responses, but they were not clear enough for me to have responded to. In the sole instance of a response, after informing the participants that I was doing a PhD and conducting research, someone asked me what I was doing and why. The other participants stopped talking, so I logged out. Unfortunately I was unable to capture this segment as it was all done in Java script. In two other chatrooms (see table 3.6) the lines following my words could have been responses to me, but they also could simply have been responses to what had been said earlier. In all the other chatrooms I was simply ignored, or at least not spoken to.

In Case Study Five, (a 5, table 4) these two responses follow my utterance:

<Neuage> ‘‘I am saving this dialogue, as long as I am in this room, to use in research on Internet Chat for a postgraduate degree. If anyone is opposed to me saving their conversation say so and I will not save the chat’.

1. 1a. <SluGGiE-> lol

2. 2a. <Mickey_P_IsMine> LoL

Whether, <SluGGiE-> and <Mickey_P_IsMine> were responding to me or to something said before I entered the chatroom is unclear. The abbreviation ‘lol’ has several interpretations [3] in English speaking chatrooms:

LOL	Laughing Out Loud -or- Lots of Luck (or Love)

Any one of these might or might not have applied to my announcement of intention to study the chat texts, so that my impact on the communicative environment remains unassessable – a timely reminder of the degree to which all ethnographic research remains problematic in relation to the issue of researcher presence, and of the relative fluidity of utterance-response relations within chat generally (see Case Studies, below). But, as throughout the field of ethnographic research generally, these issues should continue to be foregrounded as the research continues: that is, within analysis, as well as during data collection. Indeed, chat participation is in itself shot through with issues concerning varying possible, or actual, levels of surveillance, control, and regulation – the same sorts of influences attributed to ethnographic research.

There are for instance various ‘types’ of text-based chatrooms. For example, chatrooms can be divided into either moderated or non-moderated, altering the expectations among chatters as to their freedom to post whatever they wish. Moderated chatrooms can be further subdivided into chatrooms where people submit questions and answers are provided. This is most common in cases where people who are publicly known are in the chatroom, i.e. sport stars, politicians, and experts on a particular topic. Moderated chatrooms are ‘controlled’ by a particular person who controls the movement, the turn-taking, of chat. For example, if there is inappropriate language, which is considered offensive to others in the chatroom, the participant infringing can be prevented from continuing in the chatroom. Or if the ‘speaker’ wishes to dialogue on a topic that is not the assigned topic at that time, the moderator can block the ‘speaker’s’ messages from appearing in the chatroom. Nine of the chatrooms that I investigated were however open, non-moderated chatrooms, as these provided the opportunity to analyze flowing chat interactions, where participants did not anticipate regulatory intervention – although, as will be shown, such interventions do spontaneously arise within chat communities – and for varying reasons. The remaining three chatrooms were moderated, providing the opportunity to compare communicative behaviours within chat known as under surveillance, and that considered more open. The issue of my own role as a possible inhibitory influence remains less resolvable, however.

Adapting the conventions of minimal interference standard in ethnographic research, I enacted my role as online participant observer by ‘lurking’ and not attempting to direct the flow of the conversation. But more subtle levels of influence on the study are undeniably present. The list of chatrooms observed for instance has a clear bias to its selection. I chose a chatroom about Hurricane Floyd as I was an American living in Australia, and when I wished to have a chatroom that was on an emergency, I felt more competent in assessing user responses and behaviours under the pressure of extreme events when those participating shared my own cultural predispositions. I similarly chose a baseball chatroom because of a pre-existing interest: my son is a pitcher for the Los Angeles Dodgers. But given the focus of interest in these studies, unabashed subjectivity in relation to topic selection is less relevant than may otherwise be the case. Here the goal is not to construct some objectively justifiable account of online communication practices in “representative” samples of online communities, but to collect texted talk from a range of chat sites, and submit it to a number of linguistic descriptive and analytical methodologies. The participation of the researcher under these circumstances – and the circumstances of the site selections are therefore not only less problematic, but able to provide added insights into the activities encountered within the chat communities.

I had also moved on to a more complex mode of fieldwork known as participant observation, and I was getting an education I hadn't expected. Their experience of the world, their ethical sense, the ways they interpreted concepts like work and play were becoming part of my own experience (Stone, 1995).

In cyber-ethnography, the advantages of participation are less than usually counter-weighted by researcher influence on community interaction. Whilst in chatrooms, using technology hardware and software, the user is invisible: not a social actor in the usual sense of communicative relations, but a new form of social actor, intersecting actual and technologised or mediated communication: an ”actant”. Akrich argues that an actant is "whatever acts or shifts actions, action itself being defined by a list of performances through trials; from these performances are deduced a set of competences with which the actant is endowed". (1992). This view of communication as situated somewhere between the user and the machine requires a constant movement between the technical and the social a trajectory experienced as usefully by the participant-observer as by other community members, and perhaps more so, given the problems of recontacting online actants for reflective comment.

The technologisation of chat however produces other problems in relation to data analysis. Major theoretical studies have examined conversation as interaction between participants with conversation understood as spoken communication (see Stone, 1995; Goodwin, 1981). One primary characteristic of conversation is that it is fully interactive; at least two people must participate in it, and they exchange messages in ”real-time”. Participants take turns in exchanging these messages, so conversation is fundamentally a sequential activity (Nofsinger, 1991, p.3). However, online sequential activity is rare. Conversation is often similar to bumper cars in a sideshow amusement park. Dialogue seemingly bumps and weaves, often without any discernable reason for its existence. The participants seem to be "thinking out loud", expressing, without directed communicative intent. In a chatroom, turn taking has to be isolated and re-ordered in order to assemble conversation into meaning. My ”gridding” of utterances in the case studies reveals problems and mis-directions in the flow of ‘talk’. I experiment with arranging the turn-takings in rows and columns, looking for clusters of threads. I elaborate on those theories and methods of empirical research that already exist for assessing conversational exchanges in Internet-based communities (see Bays, 2000; Bechar-Israeli, 1998; Rheingold, 1991, 1994, 1999, 2000).

”The ethnographic approach emphasises the understanding of behaviour in context through the participation of the investigator in the situation being studied as an active member of the team of users involved in the situation”(Whiteside, J. 1988, p. 805). Ethnography is defined as "the acts of both observing directly the behaviour of a social group and producing a written description thereof" (Marshall, 1994, 158). At one level it can be argued that online chat produces its own written description: its own archive of talk exchanges. But, as outlined above, what appears in the screened dialogue box must be rearranged: re-sequenced, in order to reconstruct dialogic structures. And, as I will argue, it is not only researchers who undertake such rearrangements. For online chat to work at all, participants have had to evolve new skills at recombining dialogic sequences: a major key to the discursive codes of this new communicative form – and one most often reported by ”newbies” as initially alienating. In this study I will observe, analyse and present these and other discourse structures of chatroom and online discussion group cultures. In ethnography the "description of cultures becomes the primary goal... the search for universal laws is downplayed in favour of detailed accounts of the concrete experience of life within a particular culture and the beliefs and social rules that are used as resources within it" (Hammersley & Atkinson, 1995, p. 10). My study anticipates not one, but many “particular cultures” online, and seeks the possibility of generalisable regulatory system-wide behaviours only as a final outcome.

Culture’s influence on conversational styles in systematic ways or the search for a totalizing ”ethnography of communication” is a central tenet of Conversational Analysis, which examines how culturally-generated rules determine the underlying structure of conversation (see Wittgenstein, 1965). Net communities have not for the most part yet problematised either the sociological or the linguistic issues associated with online communication: that is, asked “what the rules of language let us say” or “how language is organised to let us say these things”.

Yet these communities are in some circumstances concerned with deepening their sense of cultural connectedness, establishing additional tools for intensifying the information flows. On some chatroom servers such as America Online (AOL) and Microsoft Messenger (MSN) there are methods of obtaining data on the number of people using a specific chatroom and of determining the total number of chat rooms at a given point in time. With Instant Messenger (IM) servers, as discussed in chapter one (Introduction), there is also a way to access a "profile", a personal biography stating characteristics such as age and gender as well as listing hobbies and other interests, for chat room participants who wish to make their personal details public.

The researcher’s data on the parameters of the population of online chat room users is however so far at least, limited to the above. Unless the user reveals such data within their chat, is not possible to know the age, race, or gender of chatroom users. We don't know how many people, over an extended period of time, use online chat rooms. There is no data on how long each individual user spends engaged in online chat, and we don't know at which times they are likely to come and go. Demographic information that we do have about users of online chat rooms is self-reported and unverifiable (Hamman, 1998).

An understanding of internet cultures is extended by the work of this thesis by recording and interpreting some of the ways in which meaning is produced and interpreted by strangers who know nothing more of one another than the characters they see passing on the computer screen. As I have shown in my literature review in chapter two, there has been other work done on Internet culture that addresses it as community (Rheingold, 1985, 1991, 1993, 1994, 1999 and 2000; Stubbs, 1998; Cyberrdewd, 1999; Turkle 1982, 1984, 1995, 1996) as a place of power (Poster[4], 1990; Rola[5], 2000; Schneider[6], 1997) or a place to explore one’s self (Hamman[7], 1998; Albright[8], 2000). While each of these contributes to an understanding of online ‘talk-texting’ as the relational base of Internet chat, none acknowledges the foundational act of Internet communication: in this case, its contact mechanism of rapid text exchange.

Essentially, I am interested in the meaning-making capacities of the marks on the screen as they appear, and in turn how meaning is derived from the often rapidly passing text on a screen, whether a computer or a device as small as the screen on a mobile telephone. I am concerned in this study with text-based chatrooms; however a possible heir to chat communicational conversation, SMS, is a growing field close to IRC in its techniques of using abbreviations and emoticons to communicate. One can send, reply or forward e-mail from mobile phones and users gain access using any browser and computer connected to the Internet in the world. One particular ‘snapshot’ (shown below) of who was connected via the Internet to their mobile phone showed twenty users, between the ages of 13 and 34, in ten different countries and these figures are similar to surveys of who is in chatrooms[9]. The advantage to doing research on a site that profiles users currently online is that the users’ location, age, sex and interests are revealed (providing the user provides their details accurately) whereas in chatrooms they seldom are.

Location	Age
London, United Kingdom	22
Karlsruhe, Germany	34
Kuala Lumpur, Malaysia	24
Derby, United Kingdom	14
Sandwell, United Kingdom	19
Wollongong, Australia	13
Newcastle upon Tyne, United Kingdom	16
Sydney, Australia	26
Dubai, United Arab Emirates	24
Stuttgart, Germany	24
Kolkata (Calcutta), India	24
Kelang, Malaysia	27
Birmingham, United Kingdom	23
Leeuwarden, Netherlands	14
Liverpool, United Kingdom	25
Ankara, Turkey	16
Cairo, Egypt	19
Benoni, South Africa	34
Kota Baharu, Malaysia	20
Chichester, United Kingdom	34

It is this current text-based form of communication through writing online that I believe will affect the future of communication. For example the speed of communication amongst people of different cultures, ages, gender and countries has been rapidly increasing with the use of non face-to-face interaction (see Internet Statistics. http://www.internetstats.com), as shown in the chart below:

E.U.

U.S.A.

Japan

World

Source

Number of computers1

Percent of total

141

387

ITU

Web pages2

Percent of total

13,9

3,7

65,9

23,9

4,5

3,9

94,3

1,6

Netsizer

Internet Users3

Percent of total

154

407

NUA

Mobile Phones4

Percent of total

147

39,1

31,7

481

ITU

1 Millions in 1999

2 Millions in October 2000

3 Millions in November 2000 4 Millions in December 2000

Source for the above table is from Global Experts: http://www.globalxpert.net copied January 2001.

Conversation Analysis

My study focus is on the utterances in text-based chatrooms where chatters engage in screen-texted dialogue as if it were conversation. There are other text-based chat areas, used in education and in entertainment, where character development and role-playing are more important than just turn-taking ‘talk’ sequences. Those studies that exist however focus mainly on MUDs (see Reid, 1996; Warshauer, 1995; Bromberg, 1996; Churchill, and Bly, 1999; Lisette, 1995 and Utz, 2000). These studies show that MUDs used for entertainment or education give the user the ability to construct a complex linguistic self that is in constant communication with others. These constructs are at first sight more complex than the communication in chatrooms as they also construct environments to communicate in (see Introduction to this thesis). The pragmatics of such communicative action has produced a focus on cooperative communications and community-building, which has detracted from other aspects of online talk-texting activity. A lot of research has for instance been done on the use of chatrooms for ”cybersex” (see Gilbert, 2000; Hamman, 1996, 1998). It is from these studies of MUDs and cybersexual domains that this study builds the sorts of interrelational work and collaborative structures, which can be carried into the fine-focus work of analyzing text-based chat. But some of the less well analysed areas of chat: its inherent discontinuities; its capacity for exclusivity as well as communality; its adaptation of combined verbal and visual codes and the elaboration of these into distinctive communicative forms – all of these are still under-examined.

The purpose of my selection of a ‘language-in-use’ methodology is to discover the structuring principles behind chatroom language. Internet communication is a form of rapid conversation. It is rarely ‘frozen’ for analysis, as it is when the chat is saved to examine. In other words, while my selection of chat-text makes it available for subsequent examination, it also tends to ‘reify’ it into scripted text – a direction contrary to the principles established in my earlier account of linguistic and ‘reader reception’ theories, in which I endorse a strongly active role for the act of interpretation in reception of internet chat ‘utterances’ – even suggesting that the less ‘formal’ the setting and technique, the more active and creative the meaning-making inside the exchange. By developing an analytical framework to study chatroom conversation on its own terms, as a set of distinctively different ‘speech act’ genres, I will show how the communicative act is represented when the source of the communication is unknowable. I will for instance identify differences between casual conversation used for entertainment and that found in information-seeking dialogues. For example in the first case study, ‘Storm’, because there is an emergency as the basis of the chatroom conversation, utterances occur mainly as information-seeking dialogue, whereas in several of the other case studies information seeking gambits are not present (Case Study Two, 3, 4, 5 and 7) and the ”conversation” tends to drift- or is at least differently oriented.

As online conversation is a casual form of communication, denoted by the term ‘chat’, analysis differs from studies in other generic structures (Eggins and Slade, 1997, p. 268) such as narrative (see Labov and Waletzky, 1967), gossip (Eggins and Slade, 1997) and opinion (Horvarth and Eggins, 1986).

The primary concern of conversation analysis in genres other than chat is with sequential organization, or the ways in which speakers organize their talk turn-by-turn. With online chat there is no obvious organization. It is to help focus this non-sequential organization that a method to describe this conversational genre will be developed.

Most conversation analysis of face-to-face dialogue is in the tradition of ethnomethodology, which is the careful and detailed study of how different social groups cohere around consensual behavioural practices – including the conversational exchanges used to elaborate and confirm and reinforce that consensus. (see Schegloff, 1979, 1987; Pomerantz, 1978, 1984; Jefferson, 1972).

Jellinek and Carr (1996) identify three broad purposes of conversation:

· Transacting: conducted for the purpose of negotiation or exchange within an existing problem setting;

· Transforming: conducted when individuals suspend their own personal opinions or assumptions and their judgment of others' viewpoints; and

· Transcendent: where the purpose is to move beyond or "leap out" of existing mindsets.

Within chatrooms we find all three purposes used, often appearing at once, given the technologisation of the technique of ‘posting” or entering text into dialogue boxes. Transacting or negotiation is more apparent in purpose-driven chatrooms such as in the examples I use of ‘Storm’, ‘astrology’, ‘baseball’ and ‘web-3D’. As there is more purposive turn taking in these sites, for example, to discover or exchange information, participants will often wait for a response. In Case Study One, Storm, a person inquires about the current the location of the hurricane.

[turn 74] <guest Tom> does anyone know where floyd isnow

To find out something involves a process of negotiation. In chat however, such negotiation is more than usually complex. In this turn taking example above, the answer, to <guest-Tom> could be

[turn 83] <davesbraves> 120 mi. se of cape look out nc

But maybe the answer is

[turn 103] <Werblessed> In Bladen County Outside of White Lake.

Is the answer to <guest-Tom> number 83 or 103? It would be assumed that the answer is turn taking number 83 and not 103 just because there are nine turns in between the turn 74 and turn 83 whereas there are 29 turns between turn 74 and turn 103. However, without reading all the turn takings in between we cannot know for sure, as neither <davesbraves> nor <Werblessed> addresses <guest-Tom> by name. This indeterminacy of response is just one of the new complexities in online communication.

Transforming and Transcendent turns are the least used of Jellinek and Carr’s three broad purposes of conversation, but in online chat, even transacting turns are difficult to detect and manipulate. How then can analysis move beyond this most basic of communicative relations, to evaluate the more complex elements of online meaning-making?

The methodology I propose to pursue for the textual analysis within this project is a selective mixture of several approaches to linguistic studies. As what I am proposing includes several fields of study, as shown below, I have to be clear at all times that what I am doing is at core a linguistic study. My approach to this study therefore differs from a psychological or sociological approach to the use of language. The psychologist asks why we have conversation the way we do and what are the needs of the individual which drive them to engage in a certain chatroom. Sociological conversation analysis asks what governs how we perform a given conversation, what processes are involved, and what social relations result. Linguists ask, ”How is language structured to enable us to do conversation” (Eggins & Slade 1997, p.7). By extending the detailed analysis enabled by this third linguistic approach into electronic interactions, I can retain for my study a focus on evolving practices within a sphere still loosely considered textual rather than talk-based. In other words, I anticipate the possibility of being able to capture emergent conventional patterns of use within Internet chat behaviour, as my original contribution to this field of study.

3.2 Theoretical Framework

Because of the developing diversity of chatroom talk-texting practices and their clear formation around both textual and conversational styles, this study encompasses several linguistic descriptive and analytical methods. The theories, and the chatrooms in which I apply them, include:

· Reading-response Theory (Case Study One),

· Computer Mediated Communication (Case Study Two),

· Semiotic Analysis (Case Study Three),

· Speech Act Analysis (Case Study Four),

· Discourse Analysis (Case Study Five),

· Conversational Analysis (Case Study Six), and several linguistic theories relating to discourse theories, and

· Linguistic schools of thought, which explore grammar in conversation and the construction of meaning, such as the Prague School of Linguistics (Case Study Seven).

Together these methods provide sufficient range to enable me to develop a combined method for chatroom analysis, which encompasses more of the various attributes of this set of communicative behaviours than is possible within any one of the existing “offline” frames. By selecting from descriptive and analytical techniques which can capture different facets of what is distinctive about online chat, this project hopes to create a compound strategy for chat analysis. And by selecting from methodologies which investigate language not only as a communicative system but as a tool for activation of ideas and establishment of social relations, this study aims to demonstrate that online communication has communicative efficacy: that is, operates as a significant element of contemporary social and cultural activity, rather than providing a space for trivial – and perhaps even self-delusional – “ compensatory” social connectedness. While still under formation, and yet while already demonstrating a diversifying range of sub-genres, online chat demonstrates distinctive discursive features. The method I will develop in this thesis I term an ‘Online Discourse Analysis Method’ (ODAM) which combines traditional conversational analysis theories with several features and behaviours (lurking, fleeting text, online grammar, special graphic and text-based symbols) that are particular to chatroom talk. By attending not just to the technological features which structure and constrain online communication, but to the adapted speech practices which result, I hope to reveal a richer set of adaptive talk behaviours and regulatory developments than has so far been demonstrated. With this method I will show for instance how a specialist online turn-taking is related to the establishment of a distinctive online discourse, as well as linking to various broader social and cultural discourses. The ODAM construct and its uses in examining online talk-texting behaviours will be shown in the conclusion of this study, in the hope that some of its techniques may assist in other studies of other online sites – either as these continue development, or as a record of a special moment of Internet communications history (and possibly both).

3.2.1 Assumptions

Assumptions about conversation which remain necessary to the proposed ODAM construct

Gudykunst and Kim (1997) make several assumptions whilst conceptualizing communication (pp. 6-13) which hold true in my analyses of text-based chatroom communication and are a useful guide toward a method of understanding online talk.

ASSUMPTION 1: communication is a symbolic activity

Gudykunst and Kim (1997) identify symbolic activity as occurring when "all have agreed on their common usage"(p. 6). Due to the rapid communication aspects of chatroom dialogue graphic symbols are frequently used as well as abbreviations. Because a symbol such as :) to represent a smile has no particular cultural basis in any given language, everyone easily adopts it. However, an abbreviation such as ‘btw’ (by the way) may not be as easy for someone not used to English. Therefore, chatroom conversation in other languages[10] is able to follow a pictographic symbolic convention, depicted by emoticons (see Chapter 6 in this study on emoticon similarities from other languages), while the abbreviation of words and phrases will be language specific. However, the evolution of these two systems; the degree of conventionality across and within chat ‘communities’, and the ways in which conventions evolve and are applied, will all be examined, adding to the semantic load of messages. Studying chat, in which conventions are still establishing, offers the opportunity to observe “common usage” under new pressures, and still depend on practice – that is, on actual social use, where communication-location specific symbolic systems are only partially available. To this extent, chat must be regarded as either only partially within a symbolic system or straddling dual systems of off line and online communication – or else the view of communication as a symbolic activity must in itself be modified, to accommodate the influence of material aspects – such as the technologisation of talk, or new interventions from within material culture or social contexts.

Robin Hamman’s work (1996, 97, 98, 99) on chatroom participation attempts to show how online speech is constructed, and his work will be added to the analyses enabled by the range of language-in-use analytical techniques introduced in each case study.[11]

ASSUMPTION 2: communication is a process involving the transmitting and interpreting of messages

Gudykunst and Kim identify transmitting messages as "the process of putting our thoughts, feelings, emotions, or attitudes in a form recognizable by others. We then refer to these transmitted symbols as a message. Interpreting messages is the process of perceiving, or making sense of, incoming messages and stimuli from the environment" (p. 7). With the multivocal changing threads of online chat it is necessary to identify individual chatters’ interactions to find chat chunks of an individual’s conversation. As "meaning is not static.... during the on-going flux of conversation, what will follow the speech event that is happening now is unknown" (Barnes & Todd, 1977, p. 18). Thus chat in its turn taking and technologisation problematises a simple producer-receiver model of communicative exchange.

Nor do the communicative conditions of online chat tend towards certainty in message exchange. Transmitting and interpreting several messages at once can cause confusion. If people leave the chatroom as we are quickly typing out what we want to say, we have ‘hanging’ conversations. To add to the confusion, a person may log on three times into the same chatroom using different log-on names. At some points the chatroom can disintegrate into nonsensensical communication. One aim of this study into chatroom conversation will be to establish the limits of conversational analysis within the chatroom environment. One limiting conclusion to three years of online chat analysis is that, due to the instabilities within the chatroom milieu, the analysis of conversation is not always conclusive - a limit on the ODAM research paradigm, which will be revisited in the concluding chapters of the thesis.

ASSUMPTION 3: communication involves the creation of meaning

Let us revisit here the Gudykunst and Kim proposition (pp 20-23) that only “messages” can be transmitted from one person to another. Meaning cannot be transmitted, due to its ambiguity, and to the degree of load contributed within the act of reception. With this assumption the channel used to transmit a message also influences meaning, at least in as far as it predisposes interpretation, or selects participants liable to interpret in certain ways (thus the communications technologist’s argument: 'the medium is the message'). Within chatrooms there is rarely formality in conversational exchange, which affects the form of the dialogue. There is often a sense of instability, as people come and go, at times without greetings or salutations. Texts are fleeting, moving across the limited display screen quickly. It is a medium wherein one can express whatever one is feeling at the time and not worry about the immediate social consequences of the words written. Precisely how the medium itself contributes towards or evokes such uses and behaviours will emerge within the case studies.

Gudykunst and Kim point out that if we do not know others, we use our stereotypes of their group memberships to interpret their meaning, such as their culture, ethnic group, social class and age. In chatrooms we seldom have such clues readily available, although we may still be able to decode such matters from within the utterances posted – a proposition tested within the case studies. We can also stereotype chatters by the room they are in; for example, in Case Study Seven ”baseball chat” we would assume participants are baseball fans or players and not ballet enthusiasts. Despite the comparative brevity of chat postings, there is rich evidence for complex semantic layering: plenty of space and detail for provision of cultural cues.

And yet many analysts, along with new chat participants, comment on the reduction in talk forms online. Conversations in chatrooms with others are usually carried on with short sentences. There are several reasons for this. Firstly if several people are 'speaking' at once, then it is necessary to respond quickly. Unless paragraphs of text are available to cut and paste, one is limited by both the speed at which one types, and the number of people in the chatroom. Secondly, if we do not know anyone in the chatroom short sentences may be 'spoken' in order to decrease misinterpretation as much as possible. The nature of the conversation, and its context, will always determine how brief the conversation can be. Before we say 'the Indians suck’ we have to be comfortable with whom we thought was in the chatroom, otherwise we would find ourselves being misinterpreted. Was the chatter referring to the Cleveland Indians baseball team, Native Americans, people from India, a sorority or any number of things? If we further qualify our conversation then there are fewer chances for misinterpretation. 'The Indians will never make it to the World Series', 'The Indians show no interest in baseball'’, 'I reckon Pakistan will nuke the Indians'. Any variation of the word 'Indian' can clarify a conversation: Indian club (but a club as in a group of people or a club which is shaped like a large bottle used singly or in pairs for exercising the arms?) An ‘Indian pitcher’ could mean a pitcher for the Cleveland Indians baseball team, or a native American waterpot, or to a person from Newfoundland it could represent their home (it is the floral emblem of Newfoundland); or to a botanist it could be the plant Sarracenia purpurea found east of the Rocky Mountains. Abbreviation in particular is culturally contextual in just such ways, and must therefore be examined within particular chatrooms, as well as for the whole field of chat.

Gudykunst and Kim (1997 pp 124 - 126) list Beck's (1988) five reasons why misinterpretations occur within communication, and these reasons also show at least part of the range of problems to be dealt with in chatroom conversation:

1. We can never know the state of mind - the attitudes, thoughts, and feelings - of other people.

This is clearly shown in text-based chatrooms, where we have no indication of who the other chatters are and what they are feeling or thinking, except by what they decide to post.

2. We depend on messages, which are frequently ambiguous, to inform us about the attitudes and wishes of other people.

Many messages are ambiguous in chatrooms, and because they are offered in a multilog situation, they may be differently received by different participants – or even as is often seen online, by the “wrong” participants. .

3. We use our own coding system, which may be defective, to decipher these messages.

This is discussed extensively in Case Study Three, using the analytical techniques of semiotics and pragmatics to decipher how meaning is read from signs such as emoticons.

4. Depending on our state of mind at a particular time, we may be biased in our method of interpreting other people's behaviour.

Since we are unable to access or assess the context in which postings arise or into which they arrive, the text-talk itself carries a heavier than usual load. Reception is thus more then usually active in online chat, and must be traced wherever possible in responses.

5. The degree to which we believe that we are correct in divining another person's motives and attitudes is not related to the actual accuracy of our belief (Beck. 1988, p.18).

As various Case Studies will show, some participants in chatrooms achieve dominance, such that their responses and interpretations prevail over others’. But this does not always imply that their ‘readings’ are correct, or that they lead a conversation along the lines intended by original posters or all contributors. The ‘power relations’ deployed in texted-talk need to be examined, and techniques drawn from both Sacksian CA and Fairclough’s CDA will be used and extended to do this work.

ASSUMPTION 4. communication takes place at varying levels of awareness

'A large amount of our social interaction occurs at very low levels of awareness' (Abelson, 1976; Berger & Bradac, 1982; Langer, 1978, 1989).

Chatroom conversation is not necessarily a routine part of everyday life, because a person is rarely in a chatroom because they have to be. Chatroom conversation is intentional conversation. Unlike conversation in which we engage because we need to: i.e. the person is there in front of us (a partner, supervisor, friend, neighbour, family member or shop assistant) or because we have received a letter or e-mail and need to answer; chatrooms are where we go when we really don't need to have communication with anyone in particular.

As we do not know with whom we are speaking or their background in a chatroom, our awareness of the act of communication is heightened. To be a part of a chatroom conversation we need to pay attention to what others are saying. However, due to the speed of conversation in chatrooms there is rarely the opportunity to ask someone to clarify what they are saying. People either intuit conversation or respond in whatever way seems to fit at the time. Chatroom conversation may appear to us to be one of the rare instances in human communication where there is little retribution for saying the 'wrong' thing – however as Case Studies will show, this is not always true in online communicative relations, which display as much abusive deployment of communicative power as all other forms of communication.

ASSUMPTION 5: communicators make predictions about the outcomes of their communication behaviour

When people communicate, they make predictions about the effects, or outcomes, of their communication behaviours: they choose among various communicative strategies on the basis of how the person receiving the message will respond" (Miller and Steinberg, 1975, p. 7).

Communication in chatroom is based on each participant’s pre-conceived concept of what types of people are in the chatroom. The nature of the chatroom will dictate the sort of conversation one is engaged in for the most part. Whether the chatroom is an Orthodox Christian, sexual, political, sport, or educational site, will make the conversation much more predictable. For example, a physicist wishing to chat on string-theories or wormholes in space may not find the people to speak with in an Eastern-Orthodox chatroom. The communicative strategy is to be in the chatroom that appears to be of the same mindset – or in general chatrooms, to ‘read’ the likely responses to one’s own postings, from those of earlier contributors. Analysis of online chat needs to evolve strategies to capture the “reading” strategies of participants, as displayed in how they manoeuvre within the chat strand topics.

ASSUMPTION 6: intention is not a necessary condition for communication

At the same time, Gudykunst and Kim argue that intentions are instructions we give ourselves about how to communicate (Triandis, 1977, p. 11). Intent exists in all speech situations; what is different in a virtual space is that intent is more than usually opaque, and the anticipation of concealed or subversive intent is heightened by the lack of physical contact and non-linguistic cues. Are participants there to gather information, exchange information, or play performance games? Finding intent in a chat is to determine, by following a user’s turn-takings, what the participant is doing in terms of their linguistic or discursive enactment of the communicative repertoire. To establish a method to research what is being accomplished in a chatroom I will work to identify standard categories of chat utterances, such as greetings, responses to other chatters or initiating statements. But beyond this, the often multiple possibilities of talk relations and response sequences mean that new categories need to be considered: ways of assessing utterances and sequences as less determinate than is usual, operating within a dynamic field of talk, under the pressures of a new and unstandardised technologisation, and evoking speech behaviours which may or may not establish themselves within a permanent communicative repertoire.

3.3 Protocol of a transcription methodology

Chatrooms with many interactants are ”multilogue” (Eggins and Slade, p. 24) environments. Separating these voices as conversation is a focus of this study, and something of a methodological challenge, involving the creation of new transcription protocols. As I have “captured” small numbers of turn-taking in these chatrooms I have not made use of Qualitative Data Analysis Software packages. [12]

In developing a transcription system to accommodate and "capture" IRC multilogue, I will use symbols to indicate categories of utterances between participants. I have based these categorisations on relatively established human interactions of greetings or salutations, and either questions or answers (see table below). But it is important to note that to assess turn-taking in chat according to conventional systems, there must be an addresser and the addressee who must submit to one primary turn and sequence management protocol – that of only one person ‘speaking’ at a time, as utterances are displayed on the computer screen in order of their insertion. Immediately, turn-taking in online chat complicates this relation. Nor is this the sole processing of talk which is altered by the conventions of online communication.

Assessing the addressee of an utterance is one way of guaranteeing the talk relation – yet this too is less determinate in chat. Possibilities can be coded using the following categories, to include addressing either an unidentified participant (where it is not clear who the speaker is addressing), and addressing all participants in the chatroom - which can of course also mean addressing nobody, since the indeterminacy of the relation often means that no-one feels directly addressed, and so no response is offered. The table below shows the different types of conversational relation that I have identified, which occur in a chatroom. As well as the transcription method in table 3.1 I will indicate when there is a change of topic[13] and an introduction of a new topic. Each case study uses the same coding as below.

A/ = greetings or salutations

B/ = statement- open; addressed to no one in particular, just who ever who is in the chatroom

C/ = statement - to someone named or previous (earlier) speaker

D/ = answer - to someone named or previous (earlier) speaker

E/ = answer - open - to whoever is in the chatroom

F/ = question - open - to anyone – whoever is in the chatroom

G/ = question - to someone specific or previous (earlier) speaker

?/ = undetermined or not classifiable by one of the criteria above

** = users’ abbreviations such as lol

*) = users’ emoticons in places of words

#/ = new thread or direction of talk

· A/ = greetings or salutations

According to Erving Goffman (1972, p. 79), greetings and farewells put 'ritual brackets around a spate of joint activity'. Greetings result in increased access between persons and the farewells result in decreased access. Goffman collectively designates greetings and salutations “access rituals” (p. 79ff), a subspecies of which he terms "supportive interchange ceremonies”(p. 64) or “supportive rituals” (pp. 62-94). As a form of interactive behaviour, greetings are a universal phenomenon. In any communication the desire to establish relations between 'self' and 'other' within an intercommunity greeting dispels the tension between strangers. Within a chatroom devoid of knowing who else is online a greeting shows the others the user is not going to just lurk but is desiring to be part of the chat community.

Opening a conversation in a chatroom with a greeting is standard, with <hi> showing a high degree of frequency. In face-to-face meetings greeters usually have the first topic, "How are you?" and so in the beginning, whoever greets controls the conversation. This control from greetings is problematic in a chatroom, due to the chatter being able to give a greeting at any point in time – even after having been in the chatroom (with or without the knowledge of others) for a long period of time. As the two turns below (see Case Study One) demonstrate, a user can simply say <hello all>, or he or she can add more information, as <guest-Jojo> does in turn 96. Turns 96 to 186 frame all of <guest-Jojo>’s conversation (five-utterances) in the chatroom with a greeting and a salutation.

96.	A/	24a	<guest-Jojo>	Hello Folks~~Greetings from Canada~~ How are you holding out down there?
97.	A/	25a.	<KBabe1974>	hello all
186.	A/	24g.	<guest-Jojo>	gotta run....y'all take care down there...be safe

· B/ = statement - open; addressed to no one in particular, just who ever who is in the chatroom

Opening speech functions are conversational moves which open up new exchanges (Eggins and Slade, 1995, p. 192-195) between participants. Opening moves can be greetings as noted above, or they can be used to change the topic, as discussed below in ‘new thread or direction of talk’. In a chatroom an opening move can be to get anyone in the room to respond. For example in Case Study Six <Justin> is making her or his opening, not with a salutation but with a question directed at the room:

4a.

my first visit here; what's normal?

In Case Study One, for example, the highest incidence of what I refer to in this study as chat behaviours involves statements to whoever is in the chatroom, as the table below shows.

36)

7d.

I believe this storm will weaken

This statement type does not address a specific person. As the conversation in this chatroom was about a storm <Miss Zena> is addressing the chatroom in general, and stating that it is her or his belief that the storm will weaken.

· D/ = answer - to someone named or previous (earlier) speaker

48.

6c.

Tornadoes in Pender Count

<ankash> in Case Study One is answering <guest-mandy> in turn 39 who has asked <any tornados>? The difference between this utterance and the one above it in turn 36: <I believe this storm will weaken> is that no one has asked whether the storm would weaken. <Miss Zena> is just offering an opinion.

189.

36a.

Calvin, your last name wouldn’t be Graham would it

· E/ = answer - open - to whoever is in the chatroom

In answer to chatters earlier in Case Study Onewho were inquiring where Hurricane Floyd was, <Kitteigh-Jo> in turn 13 says:

13)

4b.

<Kitteigh-Jo>

We have rain n NJ

Here a generally addressed comment also has a specific response relation.

· F/ = question - open - to anyone – whoever is in the chatroom

In other instances however, open comments invite responses, rather than offer them. For example in Case Study Six <Justin> is making her or his opening, not with a salutation but with a question directed at the room:

4a.

my first visit here; what's normal?

181)

14j.

WHERE IS THE BLASTED DEVIL AT RIGHT NOW

· G/ = question - to someone specific or previous (earlier) speaker

Questions inviting response from any participant can also be delimited to specific respondents – but to do so must use direct address:

171.

31d.

Where you at EMT?

· #/ = new thread or direction of talk

New threads or Topic are usually accomplished by a putting a space between the old topic and the new, and then opening the new with some sort of question or statement as a topic introduction.

104.

6h.

/\94

Hi guest JoJo......I'm from Wilmington the hurricane bullseye.

Table 0 ‑1 An example of a complete turn

This posting can also indicate the different types of notation this study will use to capture the complex enmeshing of individual postings within a complete chat sequence. Here, ”104” means the 104th turn in this segment. In the turns I have ‘captured’ this is the 104^th turn. What went on before these turns is not knowable, however as it is turn-104 in the captured sequence, we know that it not the first utterance in this chatroom. In fact it is the eighth turn by this person, as denoted by 6h – the 6 being the sixth person shown to speak in this extract from this room. Rarely is a log available for the complete chat. I do however have a complete log in Case Study Six, in which eight speakers entered 511 utterances – so that position 6 in an extended chat sequence could well be at the upper limit of a given chat community.

An example of a captured conversation arranged with these indicators in place shows how far the notations can assist the analyst in reconstructing the flows of postings. It should be remembered however that to the participants, sequencing and response design are decided far more quickly, and with far less information:

27) G/ /\23 2c. <dingo42> its in the AIR

28) G/ /\26 3f. <AquarianBlue> she wont be in orlando?

29) C/ /\26 3g. <AquarianBlue> sniff sniff

30) D/ /\27 6f. <Nicole528> oh yea ok

31) D/ /\28 5h. <judythejedi>i don't think so..she's bringing amtrack down maybe

31) G/ /\27 6g. <Nicole528> whats your sign dingo?

32) F/ 10a. <Night-Goddess_> anyone cool in here?

33) A/ /\32 5i. <judythejedi> hi night

34) D/ /\32 3h. <AquarianBlue> hmmmmmmm

The data for each chatroom is at:

· Case Study One http://se.unisa.edu.au/a1.html

· Case Study Two http://se.unisa.edu.au/a2.html

· Case Study Three http://se.unisa.edu.au/a3.html

· Case Study Four http://se.unisa.edu.au/a4.html

· Case Study Five http://se.unisa.edu.au/a5.html

· Case Study Six http://se.unisa.edu.au/a6.html

· Case Study Seven http://se.unisa.edu.au/a7.html

In each sample, some of the indeterminacy of online talk relations can be witnessed. What is offered to participants – and so to the analyst – is the “turn” based on the pressing of the ”enter-button”, and not necessarily the complete utterance intended. The enter button cut-off does not always constitute an utterance, since it can be mistakenly – or deliberately - pressed midway through an utterance, as the example from Case Study Six below shows. Here turn-197 is continued in turn 200:

197) B/ /\191 6p. Gordon the funny thing is

198) B/ 3nn. brian sgi visual workstatio demos by sam chen are great

199) C/ /\198 2zzz. web3dADM yeah the new SGI NT boxes come with a great VRML intro

200) --- 6q. Gordon that when I try to view those SGI vrml, or any VRML with .gz extension to it

This fracturing of an utterance is similar to ‘repair conversation’ in CA, where someone corrects what he or she has said. There are often instances of either self-initiated self-repair or of other-initiated self-repair in chatrooms. However, in a chatroom the repair may not occur for several turns. Whatever one says lies dormant and does not appear in cyberspace until the utterance has arrived through the network. . Unlike person-to-person conversation when what is said is heard instantly, even if momentarily disregarded, in a chat dialogue what is said is not “heard” until the speaker-writer wishes to reveal the content to the chatroom, and until it has traveled the distance through the system. Once the enter button is pressed there is no taking back what was said. If the chat can be saved, either by saving the screen shot of the chat or by copying and pasting or by reading the chat logs the dialogue can be ”captured” for future reference. Two examples of repair from my case studies are given below. In the first, from Case Study One, we see an example of self-initiated self-repair with <EMT-Calvin> realising that the last word of his or her utterance ended in the typographical error ”worl”. He or she changes it in turn-72 to ”work”, but only by posting the single the letter ”k”. In Case Study Six an example of other-initiated self-repair in chatrooms occurs when <Leonard>comments: <Sort night for me tonight. Gotta take my oldest to scouts> and is immediately questioned in the very next turn. Three turns later he or she responds with an apologetic explanation of what was meant by the original utterance.

self-initiated self-repair

other-initiated self-repair in chatrooms

71. B/ 1f. <EMT-Calvin> dont have to worry about someone telling me to report to worl

72. ? 1g. <EMT-Calvin> k

1. B/ 1a. <Leonard> Sort night for me tonight... Gotta take my oldest to scouts

2. D/ /\1 2a. <web3dADM> sort night? ahhhh

6. D/ /\02 1b. <Leonard Sort> == new term for Short

”D” shows that this is an answer to a previous question or statement, in this case both turns 2 and 6 responding to turn 1.

Only if the whole chat is logged and analysed can we know how many turns the person has taken in most chatrooms. In some chatrooms the time of the person entering is placed before the utterance, but this has not occurred in any of the chats that I have used in the seven case studies. Some spaces also indicate automatically when a participant arrives, but this too is not standard – one reason why chatters often announce themselves formally.

	14:56:50	\|\|\|\|\|\|\|\|\| Sascha just entered this channel
	14:57:06	MissMaca: the first plane to hit?
	14:57:12	oscar: sascha, ere you from NY?

‘911’ chat http://se.unisa.edu.au/september11/new_york_city_chat_chat.htm

To conclude the outline of transcription codings of talk exchanges:

speaker	# of entries
1. <EMT-Calvin>	34
2. <TIFFTIFF18>	1
3. <Werblessed>	11
4. <Kitteigh-Jo>	6
5. <RUSSL1>	1
6. <ankash>	16

· I use letters as to separate from the numbers, ie ”h” is the 8th letter of the alphabet)”h” after the number (eg “6’) shows the number of times this ”speaker” has spoken thus far and that this is this person’s eighth turn.

106. D/ 6h. <ankash>/\94 >12Hi guest JoJo......I'm from Wilmington, the hurricane bullseye.

· <ankash> - the brackets indicate the user name; in this case the user name is ”ankash”

· ”/\ ” means “relates to posting above”.

· ”/\ 94” would refer to turn 94 above. I do this to show that the person is referring to turn-taking 94 above, answering or making a comment, or asking about the chatter in turn 94.

3.4 Data collection

There are diverse possibilities for online text collection and collation. There are several text data mining software packages available[14] with varying methods of collecting and collating chatroom text. Technological packages maintain a permanent record of exchanges that occur in computer-mediated communication; data that is recorded automatically can be stored for future analysis (Gates and McDaniel, 1999; Mena, 1999) making computer-saved text easier to scan for patterns than verbal conversation, where CA researchers must obtain tape recordings . There are however, problems with doing online research. Firstly, there is the problem of verification. With the volume of communication in e-mail, newsgroups, and chat, manual techniques of information management are difficult to cope with. A ”sampling” protocol must be established, since entire flows of text are unmanageable for research purposes. It has been estimated that over 430 million instant messages are exchanged each day on the America Online network[15]. The obvious reductions in sample size necessitated by any qualitative method call for alternative techniques of verification – for the most part, as argued within the qualitative research paradigm, internally arising justifications built upon the rigorous application of the research analytic, and its demonstrated link into previous applications, achieving similar or related outcomes in related studies. Given the very open “sampling” technique proposed for this mixed-methodology study, such links and cross-referencing of results will also be attempted across case studies, in the attempt to build up not only an extensive survey of different sites for online chat practices, but also an intensive testing of the various methodological strategies for talk and text analysis.

Verification to this extent, seeks to establish the legitimacy of findings through comparative location of coherences from study to study – in the hope that this may help overcome the problems of verifying sources, and duplicating studies. It is for instance difficult to ‘triangulate’ inquiry methods in online research, as recommended in Denzin’s calls for “rich description” and multiple sampling techniques. Such triangulation seems ideally structured for communications research, given its capacity to survey the classic “sender-message-receiver” processing, or in Hall’s culturalist formation, moments of “encoding” (the production process) and “decoding” (reception or audience response), each locatable within the central ‘codes” of the text, But the constant flow of online chat makes it difficult to detach and extract such fully “encoded” or formed texts, while the instability and transience of online communities makes it unlikely that “reception” can be studied – at least in particular instances. Once again, this returns the researcher to the texts – but with the appropriate cautions in place, both from the methodological structures of describing the limitations of sampling, and aware of the special difficulties of studying online behaviours, given the well-established literature on the culture of identity play and even deceit, online. So, while online data collection offers some advantages -Data Mining for instance being a pattern recognition technique that does not require consent of the individual – there is at the same time a set of new problems for the online researcher. There is no method to ascertain the identity of chat participants, other than requesting an e-mail account, password and username. Data mining can assist the researcher in discovering previously unknown patterns about the word usage and topics or threads in the chatroom, but it can say nothing – or at least nothing reliable – about who those users ‘are’, where they are from, and how their online practices arise in and impact upon their offline cultural locations or selves.

Secondly then it is necessary to accede that with online data collection, the sample is not secure in its representation of any particular population (see Kehoe and Pitkow, 1996; Bradley, 1999). It is however possible to probe this issue. This study for instance deliberately chooses several special-topic chatrooms likely to attract a certain type of person, and assesses the talk-texts for distinctive patternings and recurrent behaviours. For example in Case Study Three I chose a chatsite dedicated to pop idol Britney Spears and in Case Study Seven a chatsite dedicated to baseball. By choosing topic specific sites I sought to find particular language usage, and to suggest its connection to language behaviours and discursive practices reported elsewhere, in studies of off-line communicative groups.

Thirdly, even beyond this focus on the “talk” of online chat, there is no universal method used to research online projects, generally. By some estimates, the number of studies on the Internet is more than doubling each year. The American Psychological Society[16] (APS) for instance now lists more than 80 links to online psychology experiments, up from just 10 links in 1996, the year in which the list was started. But this is still a research mode, which is under development – drawing, as does this study, on methods established offline, with all the associated limitations. Each online researcher encounters anew the problems of fitting the research tools to the research object, weighing down the inquiry process with ongoing discussion of the specifics of online conditions. For this study, given the open appropriative strategy of testing various language and text based analytics across a range of chat behaviours, this is less a problem however than a central part of the study aim. Not only is online communication of every type constrained, and perhaps differently enabled, by the conditions of online technologisation, but this study has as one of its two goals, the intention of submitting these conditions to the descriptive and analytic powers of the various research methods employed.

Fourthly, it is difficult to control the study environment online, given the broad variability of circumstances available to those who access the World Wide Web. Web users use unlimited types of software, hardware and Internet connections – so that there is no reliable way to ensure that either production or reception of online texts is the same for all users. While this study is very likely to encounter some of the communicative consequences of these variable conditions, it cannot either reduce them, or codify their presence. If online communication is often indeterminate for the user, it is even more so for the analyst. Here the sorts of constraints operating generally upon the ethnographic researcher must apply, since the data as observed and collected can only be examined and categorized in good faith, as offered to a generalised online participant, represented in this case by the researcher. This is why the analysis in this study is limited to the “texts” entered and retrieved from the sites. What participants intend, or understand, is not retrievable, except insofar as their talk strategies and techniques represent them. And while the various passes made over this text data can help clarify those representations, these are complex and often laborious analytical techniques, not available to the everyday online chat user. For instance, unraveling threads as topics or changes in topics is one challenge in identifying what a user is saying. I approach this by using several methods. Firstly I separate postings in the text by a particular user. For example, a few lines from <EMT-Calvin> below from Case Study One show that he or she is working through a self-continuing thread without much change produced by whatever else may be going on in the chatroom. In this thread <EM-Calvin> has made five utterances during a 20-turn block in this chatroom, and these can be read as a relatively coherent statement:

Chat turn	Utterance
153	folks my God is able
158	i have faith in jesus
163	if he aint done with me
164	i wont get hurt
173	thats whty i have such a peace in my heart tonigjt

But this is not the coherence offered to the chat user with their interrupted readings. Further, to read this as the sort of statement of faith it represents here, is to assume that it was produced in an integral way, while ignoring the intervening postings of others – a proposition which would have to be checked against the actual sequence of scrolling turns. Add to that the fact that the intervention of these comments within other conversations may well alter them, either in relation to accidental meaningful juxtapositions, or confusions – and these too may well influence subsequent postings. In other words, both the extraction of chat sequences by the researcher, and their subsequent analytical repositionings, are part of the reception processing of ordinary chat itself – albeit at a more complex and much slower level.

In some cases data may be excluded and disregarded altogether, for technical reasons. It is not possible to save chatlogs on some sites, due to the use of java programming or 3D software that will not produce a sequential log to research. If - as certainly seems possible – such sites are among the more up-to-date or innovative, this could well exclude whole categories of chat and chat behaviours from such as study as this – and may in turn skew results.

I collected my raw data by copying the transcription (chat-log) in each chatroom and notifying the participants. I then saved each transcription to the relevant appendix, which is online with this thesis. My data ranged from eight-minute sessions with 70 turn-takings of chat to more than one-hour sessions that had several hundred turn-takings. I saved only the text-based chat in non-java scripted chatrooms as some chatrooms preserve chat logs of what is said in the chatroom which can be viewed at a later time[17]. However since mid-2000 most chatrooms are written in java script and appear in an applet[18] which disappears once the chatroom is logged off.

Table X12

Theory used	Case study	Title	Chat-log	# of users	Turns recorded	# words	Avg. per speaker
Reader-Response Theory Reading Theory - (also - hypertextuality)	chapter 1	storm	1	45	279	2001	7.2
Computer-Mediated Communication	Chapter 2	IM	2.	2
Semiotics (Pragmatics)	Chapter 3	Britney Spears Chat Room '	3	17	70	297	4.2
Speech Act (SA) theory	Chapter 4	Astrology 'chat' ----	4	16	85	621	7.3
Discourse Analysis (DA)	Chapter 5	General chat	5	11	89	304	3.4
Conversational Analysis (CA)	Chapter 6	Web3d computer modeling 'chat' ----	6	8	511	4850	9.5
Linguistic theory schools of thought	Chapter 7	'baseball chat'	7	13	155	570	3.7

I have chosen 12 examples to try to capture a wide variety of chatrooms. The chatrooms were selected at random, however I sought themes in order to differentiate them as communities. The chatrooms were found by using the search engine ”Google”, at the time of the study the most used search engine service online, and so most likely to be used by potential chatters, seeking a themed and so sympathetic chatspace and topic. In Case Study One I copied an emergency based chatroom, where people were discussing ways of dealing with an impending hurricane in the USA. In Case Study Two, I used an ”Instant Messenger” chat, involving only two participants. For Case Study Three I used a chatroom bearing the name of a popular music star. In Case Study Four, I went to an astrology chatroom. Case Study Five was a general chatroom found on talkCITY.com. I used randomly the first chatroom which appeared in my search. In Case Study Six, I went to a chatroom in which expert discussion on ”computer animation” was taking place. I received permission from the owner of this site to use the material[19] For Case Study Seven, I used a baseball chat site, found by typing ”baseball chat” into the ”Google” search engine. I have also used three chatrooms ‘captured’ shortly after the World Trade Centre attacks on September 11 2001 as comparative examples, showing differences between moderated and unmoderated chatrooms, as well as showing people’s reactions immediately, and several days later, to a major disaster, and what online communication can offer and achieve. Two remaining chatrooms have been used to illustrate other aspects of chatroom practice as they emerge from the study. In my discussion chapter I tabulate, and comment on each case study showing the number of participants and percentages of types of conversation, such as greetings or statements to others in the chatroom.

3.5 Ethical issues

Image from http://legacy.eos.ncsu.edu/eos/info/computer_ethics /

Online research presents a number of challenges to the researcher who seeks to obtain the subjects' informed consent while maintaining their privacy. Many of the traditional research techniques and their ethical safeguards do not adapt well for use on the Internet (see Roberts, 2000; Denzin, 1999; Frankel and Siang, 1999).

In the first instance it can be argued that the anonymity of the Internet and the ease of use of pseudonyms blurs demographics, such as age, gender, beliefs, ethnicity, and country of origin, so that anonymity has extra guarantees. Some argue that capturing chatroom dialogue is not the same as collection of other online communication. As it is often impossible to know who is online in a chatroom there are no identification issues, as there would be for instance with e-mail, where once a user’s e-mail address is known they can be contacted later. Identifying the computer the person is using will not necessarily yield results as the user could be using a computer at a library or Internet Café that would show no identifying link with the actual person. And it is even claimed that this protective dissociation has impacted on how people communicate online, Studies have documented what they consider the tendency of people to become more open online than they are in person. Under a false or exaggerated expectation of privacy, participants may reveal more than they might have done under conditions in the physical world (see Reid, 1996; Childress and Asamen, 1998). If such hypotheses are correct, then ethical practices may in fact have to be even more rigorously applied, to compensate for the expectation of secure expression. However, this study, at least in part, examines whether “openness” online is universally a reality, or rests on more complex and variable foundations of discursively-established community. This research does not automatically accept therefore that the technologisation of online chat guarantees expressive security for subjects, and so takes up the usual offline protocols for human subject ethics protection.

To collect data for this study I ”lurked” in the selected chatrooms, making one entry at the beginning of each chat that I saved. When such a declaration is made, and no rejection is returned, the consent of the participants is assumed. This is standard Internet practice (See Parrish, 2000; Bechar-Israeli, 1998).

”I am saving this dialogue as long as I am in this room to use in research on Internet Chat for a postgraduate degree. If anyone is opposed to me saving their conversation say so and I will not save the chat”.

Ethical issues are an important facet of data collection and analysis. Traditional academic research that relies on human subjects is governed by ethical standards and laws designed to protect the privacy and anonymity of the individuals serving as research subjects. Because the nature of qualitative observational research requires observation and interaction with real-world social groups, ethical issues that arise in person-to-person contact are much the same as ethical issues within captured chatroom talk. Miles and Huberman (1994) list the following requirements when analyzing data taken in real-life contact:

· Informed consent (Do participants have full knowledge of what is involved?)

· Harm and risk (Can the study hurt participants?)

· Honesty and trust (Is the researcher being truthful in presenting data?)

· Privacy, confidentiality, and anonymity (Will the study intrude too much into group behaviors?)

· Intervention and advocacy (What should researchers do if participants display harmful or illegal behavior?)

This study undertook to remain aware of these issues, and to act to protect the interests of online participants over those of the researcher and research project, should such instances as those outlined above, arise.

Many online researchers currently take cyberspace to be part of the public domain, since newsgroups, bulletin boards and chatrooms are as accessible to anyone as a television, radio or newspaper interview. These researchers believe that the responsibility falls on the disseminators of the messages to filter out what they might consider revealing or private information. Hence, they adopt the position that this type of research should be exempt from the informed consent requirement (see, King, 1996). This study however, given its appropriation of methodologies developed for offline communications research, acknowledges a more integrated insertion of online talk into repertoires and expectations of other forms of social communicative exchange. It will therefore, as it begins analysis of its seven selected exemplar chat sites, work to remain aware of the very real people enacting the communicative exchanges which it will otherwise come to regard as ‘data’.

[1] These are from the field of nursing. See Should we evaluate qualitative studies –
if so, how? Online http://www.icn.ch/resnetbul05_02.htm

[2] I lurked in the chatrooms I have used in this study and did not engage in conversation except in Case Study Two where I use two examples of Instant Messenger chatrooms to show a perspective of online conversation where only two people are engaged in discourse. The term ‘lurker’ or ‘lurking’ describes one who chooses just to read the exchanges, instead of joining in the chat by posting their own messages. Most people will ‘lurk’ in a chatroom at least until they feel comfortable about joining in.

[3] I have an Internet page with thousands of emoticons and abbreviations at, http://se.unisa.edu.au/phd/storm/abreviations.htm.

[5] Rex T. Rola’s Cyberspace as A Political Public Sphere. I have saved this site to the University of South Australia server at http://se.unisa.edu.au/vc/7-cybers.htm as the original is no longer available at the address it was at.

[6] Steven M. Schneider’s PhD, Expanding the Public Sphere through Computer-Mediated Communication: Political Discussion about Abortion in a Usenet Newsgroup Submitted to the Department of Political Science, Massachusetts Institute of Technology May 2, 1997. examines a conversation about abortion that occurred within the Usenet newsgroup ``talk.abortion’’ between April1, 1994 and March 31, 1995. It tests the hypothesis that the form of discourse fostered by computer mediated discussion provides opportunities to expand the informal zone of the public sphere. Specific criteria by which a public sphere can be evaluated for its goodness of fit with the idealized public sphere described by Habermas are proposed and applied to the ongoing conversation. The conversation analyses consisted of nearly 46,000 messages written by almost three thousand authors in nearly 8,500 different threads. The public sphere created by the participants in the newsgroup was found to be diverse and reciprocal, but lacking in equality and quality. http://www.sunyit.edu/~steve/abstract.html

[7] Robin B. Hamman Cybersex Amongst Multiple-Selves and Cyborgs in the Narrow-Bandwidth Space of America Online Chatrooms online at http://www.socio.demon.co.uk/Cyborgasms.html viewed 6-2001, and One Hour in the eWorld Hot Tub: a brief ethnographic project in cyberspace at http://www.socio.demon.co.uk/project.html

[8] Julie M. Albright, Online Love: Sex, gender and relationships in cyberspace online at, http://www-scf.usc.edu/~albright/onlineluv.text Last accessed on-line Friday, 17 November 2000

[9] More than half (50.7 percent) of female chatters are under age 35, according to NetValue's research. (see http://cyberatlas.internet.com/big_picture/traffic_patterns/article/0,,5931_582491,00.html viewed Sunday, January 05, 2003)

[10] LOGOS (http://www.logos.net) has an instant International translation service and e-translation portal. The languages supported are English, Spanish, German, French, Japanese, Italian and Portuguese or in a separate chat room English, Korean and Japanese. The user must have the proper font sets installed to view Korean and Japanese characters.

[11] See The Role of Fantasy in the Construction of the On-line Other: http://www.socio.demon.co.uk/fantasy.html).

[12] Several software packages that computer-mediated ethnographers use are: ‘HyperRESEARCH’ available from ResearchWare, Inc. (http://www.researchware.com/); “NUDïIST” available from QSR International (http://www.qsrinternational.com); “The Ethnograph” from Qualis Research Associates, (http://www.qualisresearch.com/) and “Methodologist’s Toolchest (MTC),” from Scolari (http://www.scolari.com/).

[13] One of the areas I am interested in researching is how, within chatrooms the original discourse changes. I aim to isolate and analyse the 'departure points' from original topics. Though it would be impossible to know without person-to-person conversation with a chatter I be interested in a departure point is because the person comes into the chatroom with an alternative motive are whether the topic is becoming boring and is in need of a shift.

[14] In the area of automatic classification and text mining, Eidetica employs t·mining to process the content of all Flemish newspapers and enrich it with keywords every morning. The same software can be used in chatrooms to gather data over long blocks of time (http://www.eidetica.com); Miner3D is a program that turns text into 3d displays the information as sets of graphic objects spread over a space, http://miner3d.com); Upon studying the various factors influencing chat efficiency, The Virtual Worlds Group at Microsoft has developed the Status Client, a prototype of an interface that shows the status of each user, as determined by keyboard activity.

[15] B. Burkhalter, J. J. Cadiz and M. Smith. Conversation Trees and Threaded Chats. In the Proceedings of the CSCW'00 Conference. December 2-6, 2000, 97-105, Philadelphia, PA http://www.acm.org/cscw2000/

[17] In taped conversational analysis many hours of transcription time is involved, one time span I saw on a listserv on August 04, 2001 said,

(http://listserv.emich.edu/archives/info-childes/infochi/CLAN/timeestimatesre1.html)

‘I would figure about 15 hours of transcription per hour of tape recording. If you were simply transcribing words and not paying any attention to format, you could save maybe a couple of hours and this figure would be 12 hours for each hour of transcript, but then your file would not be in any consistent format.’ Saving transcription online is accurate as nothing has to be heard as it would be when listening to tapes and there would be no errors.

[18] An applet is a program written in the Java^TM programming language that can be included in an HTML page, much in the same way an image is included. When you use a Java technology-enabled browser to view a page that contains an applet, the applet's code is transferred to your system and executed by the browser's Java Virtual Machine (JVM). When the computer is turned off or the Internet site is left the applet program is no longer available until the connection to the chatroom is re-established. With a chatroom dialogue the chat is no longer available that was running before the site was left, making this a fleeting text.

[19] General Web3D Chat Log for Feb 2 2000 At

http://web3d.about.com/compute/web3d/library/chatlogs/2000/blcl020900a.htm

Blog updated 19 September 2014 K - 12 technology (updated 17 September 2014). Travel Site (2014) updated 17 September 2014. Videos/Blogs on Youtube, Twitter, Wordpress, Photo albums. Updated 15 Second Street, Round Lake, New York and photos from parent's 1943 wedding as well as Leigh's page. Farmville page updated Thursday, March 17, 2011 5:58 PM. neuage.org updated September 19 2014 10:31 PM neuage.us updated 17 September 2014 7:21 PM. Resume updated 19 September 2014

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Methodology

3.1 Introduction

Qualitative research

Research techniques

Ethnographic approach

Conversation Analysis

3.2 Theoretical Framework

3.2.1 Assumptions

3.3 Protocol of a transcription methodology

3.4 Data collection

3.5 Ethical issues

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Technology Coordinator and Computer Teacher at Dalian American International School, 2 Dianchi Road, Golden Pebble Beach, Dealian Development Area 116650 P.R. China

Blog updated / Integrating Technology Blog September 18, 2014. also:terrell.neuage.us and/or neuage.me

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