Looked at the Function of the # – lead to theory of contextualisation based on John J Gumperz conversational inference and contextualisation cues as surface feature that are verbal and non-verbal. So can be used to understand and analyse #
Cues reconfigure conversational contexts that presuppose and create context as social ordering (Bruns & Burgess 2011).
Key part of Twitter as a discourse system. Identifies four functional operators in Twitter: the RT; the @; the # and the link That have technical and communicative function as well as positioning Twitter as intertextual and interdiscursive
For data drawn from Federal State elections 2010 – 2013 over a four week period each year from parties, media, politicians, public interactions, #. Analysis uses
– profile analysis (quant)
– speech act analysis (qual and quant) (Searle), eg, inform, state, assert, announce, request etc……. Found predominately speech acts concerned with exchanging information, especially from the institutional accounts
– discourse analysis (quant informed qualitative analysis
Use case of Conservative candidate #Rottgen. But lost NRW State election and subsequntly also dismissed as Federal minister by Angela Merkel (as a ‘mother’ figure). Discourse developed as mother metaphor
# frames Tweets in to a story narrative frame that is emergent and the co-construction of meaning.
First Tweet on an April Fools as example of different types of Twitter streams – such as different communities or genres. @GregMyers on writing on blogging realised that there is not one ‘thing’ of a blog – share a media but are very different. Are we talking about one genre or not? Looking at the different papers at the conference it is clear that there is not a single genre or function.
How do different Twitter communities use Twitter? Are there genre differences. Focus here on science Twitter of research scientists.
Networking is a part of any science project from the 16 century onwards. But as a community, depend for reward on the production of a very different text object, the published paper which is very unlike Twitter. So science community is a network of texts but also involving equipment, people, methods, money (ANT).
Identified two themes of sociology of science:
1. heterogeneirty of scientific networks: ANT. You become powerful in science by maintaining a network
2. rhetorical tension between empiricist repertoire as timeless claims in the formal literature and a contingent repertoire and time bound and contingent activities.
Cites letter from C19 that is very Twitter like albeit as provate letter rather than a public Tweet.
More information on Greg’s blog: http://thelanguageofblogs.typepad.com
Corpus analysis based on keywords eg, paper, scientist, research, etc… but more interesting keywords such as: over use of “i” (compared to other Tweets) as a sign of formality; use of “of” as signifier of more complex; “but” as academic signifier and a negative keyword of “love” as evaluation.
Gives ground to identify scientists as a distinct community on Twitter.
Gives an example of phatic communication – communication for the sake of contact (“who is still working” at 3 am). Problematises the use of the term “here” as “a lab” rather than a geographic co-location. Solidarity building?
Particular interest in references to time: current time – what I’m doing now; temporal cycles of, eg, work , publications, terms; future time (what will be happening); and chunking time eg, pleistocene.
Gives example of scientific criticism and never-ending use of citations and references but also criticism of socio-thermodynamics using LOLcats
Scientific criticism involves personal stance; impersonal references to shared norms and hierarchies of authority for presentational purposes. Found many Tweets involve boundary work, sealing off science and non-science while at the same time concerned with outreach and public engagement with science.
Good set of question of a Twitter community:
- present self as a community?
- make a distinct genre – eg, use of RT, links etc…?
- use the same genre / register?
- how Twitter practices relate to other practices?
- what specific kinds of performance are valued?
- how permeable are the boundaries of the community? How many Tweets get RT from outside the community?
Permeability of the science community enhanced as scientist may be member of other communities that may cross-overs of their specific Tweets (hip hop, feminism/ women in science). But not seeing non-scientists coming back and commenting on scientific discussions.
The afternoon session is about to kick-off with Noreen Dunnett on The Tweeting Zone with Twitter providing a mechanism for renegotiating boundaries between Activity Systems. Looking also at how Twitter allows renegotiation of identities and roles of learners and teachers in formal learning spaces.
Referes to liminal spaces as a rite of passage in which a person moves from one state of being to another. Could Twitter affordances at act bridge between Activity Systemas a a boundary zone between different systems and spaces? Does Twitter provide scaffolding between learning and working definitions.
Affordances (actionable properties …. user perceives some action is possible. Gibson 1977, 1979 and Norman 2004). The paper uses Connectivism and Activity Theory examining a teacher training course and the student use of Twitter ordered around a given #
Frames Twitter in terms of a Personal Learning Environment (PLE) as allowing learners to coordinate arrangements between people, materials and technology so the PLE is not a platform but is rather a process that requires agency from the learner [as actor].
Uses ethnographic action research including participant observation, interview and survey. Observation of a Twitter chat over a seven month period with researcher moderating initial discussion. Spaces of learning in, eg, Twitter, enacted in to being – emerge rather that design/ predetermined (Al Mahmood 2008).
Cited example of student who left the course asking for permission to continue to use the hashtag.
Trainee teachers participate in a range of discourse communities simultaneously, spanning formal and informal learning environment. The course tutor conflicted about Twitter and the degree of control and policing role.
Useful Tweet here:
Twitter bridge Activity Systems as discourse communities.
Role of tutor not clear: has emergent and non-emergent elements as the Twitter space was formally set up to support students in placement but tutor also wanted to use it for learning tasks by setting up a series of tasks Tutor was concerned that the students controlled by eg, GTC notions of professional conversation.
References from the presentation can be found here
Now out of power and seeking a plug point ……
Used Martin Hawksey’s TAGs for grabbing #feeds into Google Docs.
Social media collaboration group came into being to analyse Tweets on London riots using manual analysis and wanted to use more automation in the analysis. Clare developed a prototype as the JISC Twitter Workbench initially for analysis of Olympics on Twitter but extended in to more general academic use. Currently working on developing the Workbench to work with smaller, discreet data including elimination of direct (unchanged) RTs. Testing Workbench for use at a conference (done aferwards but could be done in real time).
At the conference, was a lot of interest in, for example, PechaKucha and specific talks that gained a lot of interest.
Found different algorithms appropriate for different size of event/ Twitter hashtags. Clusters confirmed some hunches about the conference.
Noted that clustering does not analyse influence of a Tweet. Confirmed participant feedback on conference sessions. Did identify what was popular (not influential?) and ‘hot topics’ etc which could have been very useful for real time use eg, in back channel. Could imply unpopular sessions not Tweeted but this is not clear.
Very clear decline in volume of Tweets after conference – often sharing links.
Analysis was about the content of Tweets and not about connections between Tweets…
Balance to be developed between clustering duplication versus clustering granularity.
Q of why JISC funded this given the existence of NodeXL
Now time for a break….
Fell behind on the blogging – lack of power, fat fingers etc….
Discussing finding the time for Twitter and intensity, @johnnyunger very variable in intensity of Tweeting. Mentions that avoiding marking leads to increase in Twitter use.
A number of comments in Tweeting in between times
Tweet when we’re doing other things or when can’t do other things
But also comments about the rhythms of the day – energy, roles etc…
… and in relation to activities in “real life” (sitting on the bus) as well as on other SoMe.
Discussion on whether Twitter is distracting or takes time [but avoids issues of cognitive-shifting]
Moving to ethics, eg, is it OK to be anonymous on Twitter and issue of institutional constraints. Also scales of anonymity, eg, less easy to identify the individual rather than anonymous per se.
Comment on analysis of HE SoMe policies that are very constraining requiring various disclaimers for staff. HE senior management prickliness on potential reputation harm from ‘rogue staff’.
Comment that first rule of the internet that there is no such thing as anonymity – don’t say something online you wouldn’t say elsewhere (from @pennyb).
Moved on to impact – beyond simply number of followers but also who follows.
Discussion on ethics and the nature of public domain with good understanding of the nuances around anonymising Tweets. Also refering to Twitter TOS in tension with research ethics, eg, on anonymity.