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
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).<SPAN
style="mso-spacerun: yes"> </SPAN>However, on-line sequential activity
is rare.<SPAN style="mso-spacerun: yes"> </SPAN>Conversation is often similar to
bumper cars in a side show amusement park.<SPAN style="mso-spacerun:
yes">
</SPAN>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.<SPAN style="mso-spacerun: yes"> </SPAN>It is rarely ‘frozen’ as it is when
the chat is saved to examine.<SPAN style="mso-spacerun:
yes">
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.
<SPAN style="FONT-FAMILY: Arial">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></SPAN><SPAN
style="FONT-FAMILY: Arial"><![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
Coordinated
Management of Meaning - W. Barnett Pearce & Vernon Cronen
Symbolic
Interactionism - George Herbert Mead
Nonverbal Messages
Expectancy
Violations Theory - Judee Burgoon
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 participant will
be represented by *. The codes will be in brackets following the text. [ #].
Note that the numbers represent the line of text, not the speaker.
EXAMPLE
I.
1.
Janis> Through now I know we are part of the universal plan to exist on the
third dimension, but why was there such a plan for us to exist in the first
place. [#]
2.
dammit>(Singapore) hi janis [*]
3.
steven> hi janis, dammit! [*] Just wanted to dropped in home-- after
splatter painting my consciousness throughout the multi-verse for eons, it is
nice to be here! [ 3Ù 1]
4.
steven> Janis, I see this no thing, some thing is like a pendulum/fulcrum
swing. Tell me more about lexigrams--sounds fascinating! [4Ù 1]
5.
1love> curtis, thanks for your photo, [*] this mustard seed looks all golden
to me! My photo is on its way, just got the pics back NEW SITE = JULY 2014 - http://neuage.us/2014/July/ - Today. [#]
The
above would be coded thus: #1, 3Ù 1, 4Ù 1, #5.
The above
dialogue was take off of the 'Time Traveller' web page: http://time-travelers.org/chatt.htm
Here the
"out of step" narrative of the multilogue is clear. An attempt for
instance to schematise the interconnections of the 4 speakers would include
retrograde as well as forward directions - and include some references not in
the current "dialogue box" (or "multilogue" box). To show
how contributors and readers manoeuvre within such a system of exchanges I will
need to develop a protocol model similar to CA to diagnose speech and to find
how readers and writers understand, interact and continue. There are several
models to build upon but I will use the pluri-semantic model of Kress and van
Leeuwen and O'Toole (cf. Kress and van Leeuwen 1990, 1996, O'Toole 1994) in
Eggins and Slade's work (1997, p.49). The pluri-semantic model is outlined
below, giving three main approaches to analysing casual conversation:
ideational, interpersonal, textual.
Types of
meaning |
Gloss/definition |
Examples:
above Ex. I |
Ideational |
Meanings about
the world, representation of reality (eg. topics, subject matter) |
Conversation,
expressions; the universal plan - #1 |
Interpersonal |
Meanings about
roles and relationships (eg. status, intimacy, contact, sharedness between
interactants) |
4Ù 1 share
meanings 5-?
Relationships undefined 2Ù 1
greetings/contact 3Ù 1,2
contact/greetings 3Ù 1 shared
meanings through metaphysical 'talk' |
Textual |
Meanings about
the message (eg. foregrounding/salience; types of cohesion) |
1 positioning
the conversation ideologically 3 continues
metaphysical meaning of 1 5 breaks own
conversation into two (re. Photos) by inserting text about mustard seed. |
(Schema
modified from Eggins and Slade 1997, p.49)
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. Does the person come into the chatroom with an alternative
motive? Is the topic becoming boring and in need of shift? And who are the
people who are speaking? Some people have a link to their 'homepage' which may
contain more information about the person, but as Daniel Chandler says in his
"Personal Home Pages and the Construction of
Identities on the Web"
(http://www.aber.ac.uk/~dgc/webident.html) .
..the
created 'textual self' is how the author wishes others to see them. "The
medium of web pages offers possibilities both for the 'presentation' and
shaping of self which are shared either by text on paper or face-to-face
interaction.
This
suggests that the 'textual self' can present itself as a less constructed
"reality" in the constructed exchange of On-line presentation. But
whether 'textual selves' operate the same in chatrooms and IM as they do in
one's homepage needs to be researched before a conclusion can be known. I
hypothesize that people create a different 'textual self' for each environment
they are in, and that we should not continue to regard all electronic textual
practices as equal.
Like
other areas of the Internet, chatrooms too have etiquette, and rules of
cybersense are continuously evolving. Jill and Wayne Freeze point out in their
book Introducing WebTV,
..that what
is written is not always what is meant. A fair amount of meaning relies on
inflection and body language. It is best to clarify a person's intentions
before jumping to conclusions or getting defensive. (p. 135).
"Rules"
are however already established in IRC - for instance, the convention that
capitals imply shouting. Other, more subtle conventions also are developing, as
well as abbreviated "talk" (see notes on 'abbreviations in chatrooms'
10).
NOTES AND
REFERENCES FOR THE METHODOLGY SECTION
An
article on analyzing tape recordings. Time
estimates for CHAT & CLAN " If the goal of the
transcription is basically to "get the words right", I would figure
about 15 hours of transcription per hour of..."
CHATROOM ABREVIATIONS – a much larger database of
emoticons and abbreviations are saved at:
{{{{{{}}}}}} cyberhugs. {{{{{Terrell}}}}}}}
:) a smiley face denotes that you are joking or happy. there are many
variations on this such as :-) ;-) :0 so keep smiling
:( a sad face. this too has variations of despair that can be added such
as :(~~ for crying and :P~~ giving someone the raspberry
>:) at its mildest is someone who is mischievous and at its worst...a horny
devil.
0:) an angel...
<s> is a tiny smile
<S> a huge smile
<g> is a grin and to make it a bigger one, use a capital g.
<eg> evil grin
<weg> wicked evil grin?
<vweg> very wicked evil grin for those people who are
not faint of heart.
<bfg> big freaking grin
<snicker>
<giggle> <tee hee>
<gag> <choke> <hack> <cough>
LOL laughing out loud
lmao laughing my ass off
pita pain in the ass
btw by the way
fyi for your information
imo in my opinion
iyo in your opinion
brb be right back
bbiab be back in a bit
bbl be back later
afk away from keyboard
^5 high five and means you're congratulating someone on a comment they
[1] Another transcription method of Internet chat is shown at: http://se.unisa.edu.au/phd/thesis/transcription.htm