Issue mapping Inside Out

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Presentation by Noortje Marres & Carolin Gerlitz (Goldsmiths, University of London) at The Co-Production of Knowledge: Social Media, STS and ... conference, University of York, July 18 2012

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Issue mapping Inside Out

  1. 1. Issue Mapping Inside Out The Co-Production of Knowledge. University of York, July 19 2012 Noortje Marres & Carolin Gerlitz Goldsmiths, University of London
  2. 2. Issue Mapping• Issue Mapping offers methods & techniques for theanalysis of topical affairs.• Builds on controversy analysis.• Developed in the field of Science, Technology andSociety (STS). (Callon et.al, 1986; Barry, 2001; Latour,1988; Bloor, 1982)• Empirical, processual approach to studying relationsbetween technology, society, science, politics...• Asks: Is this topic an issue? Who are the actors?Where is it based? Where is the issue happening? Howdoes it change?
  3. 3. Issue Mapping Online• Digitization offers opportunities for issue/controversy analysis (Rogers & Marres 2000,Latour et. al 2007, 2010; Yaneva 2007).• Explosion of traces and of analytical devicesdeploying traceability.• Our project builds on existing approaches:mapping controversies, real-time research,digital methods.• A special focus on taking advantage ofspecificity of online media for issue mapping.
  4. 4. A participatory method?• Issue mapping online as assembly of tools,methods, devices & actors.• Methods become distributed and henceparticipatory: method as collectiveaccomplishment.• Issue Mapping Online seeks to deployanalytical capacities of tools, data formats,designers & issue professionals andresearchers. www.issuemapping.net
  5. 5. Tactics of issue mapping• Issue mapping as modular method: notindividual tools/devices/methods matter, butthe relations created between them.• Strategies vs. tactics.• Tactics as inherently contextual: giveconsideration to issue, medium and moment.
  6. 6. Tactic: studying liveliness• Specific response to growing interest inreal-time/live research.• Liveliness: variation in issuecomposition over time.How to study change?• As opposed to liveness: currency orhotness.How to study popularity?How to study the happening of issues?
  7. 7. 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 innovation dynamics(Callon et.al 1983) & happening of content (Danowski 2009; Marres &Weltevrede 2012).
  8. 8. 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 & internalrelations.Project conducted during the Co-Word Workshop,(Goldsmiths) and the Digital Methods SummerSchool (Amsterdam) 2012.Noortje Marres, Carolin Gerlitz, Esther Weltevrede,David Moats, Sara Kjellberg, Tally Yaacobi-Gross,Jill Hopke, Kalina Dancheva, Diego Dacal,Alessandro Brunetti, Johannes Paßmann, AlbrechtHofheinz, Colleen Reilly, Erik Borra, BernhardRieder.
  9. 9. Hashtag lifelines 2. Variation of key1.The limits of frequency hashtags over time3. Hashtag profiles 4. Associational profiles
  10. 10. 1. The limits of frequencyQUESTION: What are the top hashtags per interval and howdo they vary over time?SELECTION: 1) Frequency measures 2) Co-word analysis
  11. 11. !" #!!" $!!" %!!" &!!" !!" (!!" )!!" *!!" +!!" #!!!"!#,!%,#$"!%,!%,#$"!,!%,#$"!),!%,#$"!+,!%,#$"##,!%,#$"#%,!%,#$"#,!%,#$"#),!%,#$"#+,!%,#$"$#,!%,#$"$%,!%,#$"$,!%,#$" issue transformer).$),!%,#$"$+,!%,#$" Top hashtags per day.%#,!%,#$"!$,!&,#$"!&,!&,#$"!(,!&,#$"!*,!&,#$" • Bursts have short durations.#!,!&,#$"#$,!&,#$" • Frequency helps to understand#&,!&,#$" • Question of medium-specificity.#(,!&,#$" what is a hashtag (publicity device,#*,!&,#$"$!,!&,#$"$$,!&,#$"$&,!&,#$"$(,!&,#$"$*,!&,#$"%!,!&,#$"!$,!,#$"!&,!,#$"!(,!,#$"!*,!,#$"#!,!,#$"#$,!,#$"#&,!,#$"#(,!,#$"#*,!,#$"$!,!,#$"$$,!,#$"$&,!,#$"$(,!,#$"$*,!,#$"%!,!,#$"!#,!(,#$" !"#$"%#&()*+,-./012&%.3)4.-56%7/.#/89-56%7/.#53/80#:!%,!(,#$"!,!(,#$"!),!(,#$"!+,!(,#$"##,!(,#$"#%,!(,#$"#,!(,#$"#),!(,#$"#+,!(,#$"$#,!(,#$" -7$" -BCDB" -HIEE@" ->?@A?" -14673/" -@EFGEAD@" 1. The limits of frequency -./012./345" -HJDG?JF?IKL@H" -0289:32;02<" -6180<=01:.<9."
  12. 12. 3. Hashtag profilingWhat is the issue space animated by?Qualification of HashtagsElements of hashtag profiling• URL profiling: identifying & categorising hostsmentioned together with hashtag.• Actor profiling: identifying key actors using thehashtag.
  13. 13. 4. Associational profileIdentifying hashtag lifelines throughassociational profiles.• Associational profiles: Detectchanging co-hashtag relations overtime.• Which hashtags co-occur with eachother?• Stable or fluctuating associations?
  14. 14. Comparison #environment & #drought
  15. 15. Conclusion• 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 itempirically?
  16. 16. Questions? n.marres@gold.ac.uk c.gerlitz@gold.ac.uk

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