methodology

Methodology Wednesday, 20 February 2002

Development of a protocol of a transcription methodology –

Types of Chatrooms

Grammatical patterns in chatroom 'talk' including use of abbreviations and emoticons

How roles change in a chatroom 'talk'

Patterns of interaction in chatroom 'talk'

How moods are established or/and changed in chatrooms

The use of abbreviations and emoticons in chatrooms

chat-table

These hypothesis can not be answered using quantitative analysis, as there is not a way at this time to know who is in what chatroom. I discuss the problems associated with attempting to answer these hypothesis in the Methodology Chapter and suggest areas for further research.

No Terrell, you outline them here and discuss them in your methods chapter. These are problems you had to face and had to deal with to devise a method of analysing chat. Your method is a significant contribution to research but it doesn’t belong in your conclusions chapter. Your conclusions should summarise what you concluded as a result of your study.

Major theoretical studies have examined conversation as interaction between participants with conversation understood as spoken communication. One primary characteristic of conversation is that it is fully interactive - at least two people must participate in it, and they exchange messages in a real-time basis. Participants take turns in exchanging these messages, so conversation is fundamentally a sequential activity (Nofsinger 1991: p.3). However, on-line sequential activity is rare. Conversation is often similar to bumper cars in a side show amusement park. Dialogue seemingly bumps and weaves often without any reason for its existence. There is a sense that participants are "thinking out loud". In a chat room, turn taking has to be isolated in order to assemble conversation into meaning. What I will attempt to do with my methodology is to elaborate on the theories and methods of empirical research that already exist in both conversational analysis theories on the Internet and on Internet-based communities such as diverse types of chatrooms. Finding how internal meaning is transmitting is a primary concern of chat room conversation. How are words or objects (using emoticons) linked to create a semantic chain to produce an identifiable and answerable sequence?

Chatrooms have limitations that conversations in which physical speech is produced do not have. Talk in chatroom is limited to short phrases. Rarely will there be more than several words written at a time by a 'speaker'. Looking at a sampling of a dozen Chatrooms and hundreds of entrances I found that there was an average of 7.08 words per turn. Within that sampling 25 percent of words consisted of two letters, and 20 percent consisted of three letter words. Eighty-three percent of words used in chatroom conversations were five letters or less. The way we will communicate will change and is now changing. As we are faced with more choices and more to do all the time communication will become more concise or the speaker will be left behind.

There are millions of chat rooms catering to all possible human interaction. A majority of chat rooms become seemingly stuck in the ‘hello’ or ‘anyone want to chat privately’ categories. The chat rooms I am analysing are rich in turn-taking and developed conversation. This chapter on ‘storm’ a study in chat room linguistics during an emergency is my starting point in working with an on-line linguistic.

<![if !supportEmptyParas]><![endif]><o:p></o:p>The purpose of my methodology is to discover the structures of chat room language. Internet communication is rapid conversation. It is rarely ‘frozen’ as it is when the chat is saved to examine. By developing an "analytical framework" to study chatroom conversation, I will identify differences between casual conversation and information-seeking dialogues. This first study, ‘Storm’, is mainly of the information-seeking dialogues framework.

The methodology I propose to pursue for the textual analysis within this project is a mixture of several approaches to linguistic studies. As what I am proposing to do 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. And within that framework discover the impact of text upon real events. 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. Sociological conversation analysis asks us instead how we do the conversation. Linguists ask, "How is language structured to enable us to do conversation" (Eggins & Slade 1997, p.7). By extending this 3rd, 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.<o:p></o:p><![if !supportEmptyParas]>

In developing a transcription system[1] to accommodate and "capture" IRC multilogue, I will use symbols to indicate: interaction between participants, change of topic, and introduction. The example below is a generic format. Each case study will have a different method for analysis of data. This is because I am using different theories and looking for different interpretations of meanings in each chat room.

I will analyse chatrooms using

Reception and Reader - Response Theory and Reader Theory’ (Umberto Eco (1979, 1986, 1995), J. Kristeva (1980), Michael Payne (1993).) See Case Study 1 http://se.unisa.edu.au/phd/storm/chapter1.htm)

Speech Act Theory (Jurgen Habermas (1989), John Rogers Searle (1965, 1969, 1976), Deborah Schiffrin (1987), Terry Winograd (1986). See Case Study 2 http://se.unisa.edu.au/phd/storm/chapter2.htm)

Discourse Analysis (Norman Fairclough (1989, 1995), Bakhtin, See: Case Study 3 http://se.unisa.edu.au/phd/storm/chapter3.htm)

Conversation Analysis (Diana Slade and Suzanne Eggins (1997), Donald Allen and Rebecca Guy (1974), John Austin (1962), Erving Goffman (1959), H Sacks (1974), E. Schegloff (1974), Deborah Tannen (1989). See Case Study 4 http://se.unisa.edu.au/phd/storm/chapter4.htm)

Semiotics and Pragmatics (Chandler, Barthes, Halliday, Saussure, M. A. K. Halliday (1978), S.C. Levinson), Nofsinger (1991). See Case Study 5 http://se.unisa.edu.au/phd/storm/chapter5.htm)

Linguistic schools of thought: (See: Case Study 6 http://se.unisa.edu.au/phd/storm/chapter6.htm).

Computer Mediated Communication including: Electronic Communicated Analysis, Computational Linguistics and Text and Corpus Analysis (Charles Ess (1996), Michael Stubbs (1996) See Case Study 7 http://se.unisa.edu.au/phd/seven/introduction.htm).

(note - Verbal Messages http://www.ic.arizona.edu/~comm300/mary/messages/index.html

Information Theory - Claude Shannon & Warren Weaver

Meaning - I. A. Richards

Coordinated Management of Meaning - W. Barnett Pearce & Vernon Cronen

Symbolic Interactionism - George Herbert Mead

Nonverbal Messages

Expectancy Violations Theory - Judee Burgoon

Semiotics - Roland Barthes

The individual methods for each study are at:

Case study 1 storm http://se.unisa.edu.au/phd/one/method.htm

Case study 2 Astrology 'chat' http://se.unisa.edu.au/phd/two/methodology.htm

Case study 3 General chat http://se.unisa.edu.au/phd/three/methods.htm

Case study 4 ’Web3d computer modeling 'chat' http://se.unisa.edu.au/phd/four/method.htm

Case study 5 ‘Britney Spears Chat’ http://se.unisa.edu.au/phd/five/method.htm

Case study 6 'baseball chat' http://se.unisa.edu.au/phd/six/method.htm

Case study 7

analysis

In the below example of interaction between participants I will indicate retrograde speech referencing, as "speakers" can only refer to what has already been said. For example, in the multilogue below, the text in 1 is not answered until 4. Indicating this interaction will be coded 4 1. For a new topic/thread the # symbol will indicate the change. For example 'speaker' in text 5 jumps into an already existing conversation and may be changing the topic - it will depend on what follows whether '1love's' change will begin a new thread or will be ignored. To indicate this change it will be coded #5. This will be demonstrated more in example III and IV. To indicate a speaker not speaking to a known participant, such as 5 'speaking' to 'curtis' who is not in the immediate conversation, I will write 5-?. Greetings to a new participan