la sociología en twitter
TRANSCRIPT
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Doing Sociology with Twitter:
Digital Ethnography Week, Trento
September 19 2012
Noortje Marres
Goldsmiths, University of London
Actor profiles and issue lifelines
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Doing Sociology with Twitter:
Doing Sociology with Twitter?Issues of ownership and control in live social research....
(or: challenges to methodological sovereignty)
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Digitization is enabling new ways of organising social life as well as of
analysing it (Law, Ruppert and Savage, 2010)
Digitization may also reconfigure the relation between social life and its
analysis (Rogers, 2010; Kelty, 2008)
The facilitation and analysis of social life intersect in potentially new
ways in digital platforms:
How does this affect the relations between the object, methods and
concepts of sociological research? those between data, techniques
and methods?
The case for digital sociology..
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The promise of digitizationfor sociology -
some explanations
- Explosion of social traces and of analytical devices
deploying this traceability of social life (Beer, 2012)
- Digital platforms materialize sociological concepts
and phenomena, such as the performance of the
self (Hogan,2010) or actor networks (Latour and
Venturini, 2012)
- Real-time research: digitization highlights the
potential of social research techniques to intervenein social life (Back and Lury, 2012).
Do these explanations consider the changing divisions of
labour in digital sociology - if so how?
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Digital techniques play a key role in formatting the empirical object ofsocial research: this affects the division of labour in social research:
1) it changes the distribution of agency between data, technique,method (eg the data organise the research design)
2) to do research with digital platforms is to import categories thatare native to the medium into social research
How to render this productive for social research, derive analytic
capacities from the medium for sociological research?
The re-distribution of social research
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Twitter and the re-distribution of socialresearch methods
Twitter bears some similarities with participatory traditions in social
research, such as the mass observation movement (Savage & Burrows,
2009):
non-sociologists (users) act as observers
Twitter as an analytic apparatus poses constraints:
restricted data capture, opaque sampling the tweet as unit of
analysis, the phenomenon of the trend
The challenge for sociological research:
How can Twitter as a research apparatus and analytic culture be
re-purposed for sociological analysis?
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re-purposing Twitter for socialresearch?
The rise to prominence of live research: thetracking of the currency of actors and issues
in real-time
Liveliness: Can we analyse the activity ofissues in other terms than currency?
As opposed to liveness: currency or hotness.(How to study popularity?)
Tyranny of frequency vs. the happening of issuHow to study the happening of issues?
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Case study : Lifelines of issue terms
Focus on hashtag mining as
technique for analysing variability of
issue terms over time.
1. Are hashtags a suitable format for analysing liveliness of issue terms?2. What are the possible alternatives for frequency analysis?
Rather than defining what rises and falls (Downs 1974), we may detect what isactive and changes in association.
Co-word analysis: methodological strategy to study innovations dynamics(Callon et.al 1983), and happening content (Danowski 2009, Marres &
Weltevrede, 2012).
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The Dataset
Twitter data for Climate Change.
Period: 01.02. - 15.06
Interval: six 2 week intervals
Total 204795 tweets.
Focus on hashtags, their variation &internal relations.
Project conducted during the Co-word
Machine (Goldsmiths) and the Digital
Methods Summer School (Amsterdam)
Noortje Marres, Carolin Gerlitz, Esther
Weltevrede, Erik Borra, David Moats, Sara
Kjellberg, Tally Yaacobi-Gross, Jill Hopke,
Kalina Dancheva, Diego Dacal, Alessandro
Brunetti, Johannes Pamann, Albrecht
Hofheinz, Colleen Reilly, Bernhard Rieder.
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1. Hashtags over time
QUESTION: What are the top hashtags per interval and how
do they vary over time?
SELECTION: 1) Frequency measures
2) Co-word analysis
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Top hashtags per day. Bursts have short durations.
Frequency helps to understandwhat is a hashtag (publicity device,
issue transformer).
Question of medium-specificity (onTwitter issues are likely to last a day)
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Overview'Top10'#tags'(without'#climate'and'#climatechange)'
#CLEANCLOUD"
#AUSPOL"
#ENVIRONMENT"
#P2"
#SAVETHEARCTIC"
#qanda"
#tcot"
#newbedon"
#green"
#globalwarming"
1. The limits of frequency
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Co-word analysis
Brings Network analysis to bear on textual data.
Focus on co-occurrence of terms, hashtags,
keywords.
Detecting emergence of new terms in relation to
other terms
Methodological strategy to study happening content
(Callon et.al 1983; Danowski 2009).
An alternative to word frequency analysis?
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4. Actors profiling
What techniques can we use to further qualifythe issues?
can we use associational logic to produce
typologies of hashtags?
Elements of hashtag profiling
URL profiling: identifying & categorising hostsmentioned together with hashtag.
Actor profiling: identifying key actors using thehashtag.
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3. Associational profile
Identifying hashtag lifelines throughrelational profiles.
Associational profiles: Detectchanging co-hashtag relations over
time.
Which hashtags co-occur with each
other?
Stable or fluctuating association?
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Associational profiling
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Comparison #environment & #drought
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Conclusion
www.issuemapping.net
How does media liveliness map into issueliveliness?
Media-liveliness: bursty hashtags, hashtagdecline.
Can we conceive of medium-specificity and issue
specificity as a spectrum?
Can we establish it empirically?
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Thank you.