seminar at Australian National University

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seminar at Australian National University

  1. 1. Political communication and social media Maurice Vergeer Radboud University Nijmegen m.vergeer@maw.ru.nl www.mauricevergeer.nl @mauricevergeer
  2. 2.  1992-1996 ◦ department of communication 1996-2000 ◦ department of methodology 2000-2004 ◦ Dutch Media Authority 2004- ◦ department of communication 2009-2011 ◦ Yeungnam University, Gyeongsan, South KoreaCV
  3. 3.  Political communication ◦ My research Theory ◦ Social capital ◦ Personalization ◦ Political playing field / innovation vs normalization vs equalization Methodology ◦ Content ◦ Actions / behavior ◦ Unobtrusive measurements ◦ Time series analysis ◦ Cross-national comparative analysis Issues and challenges ◦ Spam accounts ◦ Issues related to the APIoutline
  4. 4. Web feature analysis
  5. 5.  Norris (2001) Foot, Schneider, Kluver & Jankowski (2007)Web features
  6. 6.  Norris P (2001) Digital Divide? Civic Engagement, Information Poverty and the Internet Worldwide. Cambridge: Cambridge University Press. Foot KA, Schneider S M, Kluver R, Xenos M and Jankowski NW (2007) Comparing Web production practices across electoral Web spheres. In: Kluver R, Jankowski NW, Foot KA and Schneider SM (eds), The Internet and National Elections. A Comparative Study of Web Campaigning. London: Routledge, 243- 260.
  7. 7. Informing InvolvingAbout the producer Discussion forumIssue positions Join/become a memberInformation about campaign process Get e-mail from siteInformation about voting process Information about donating money Opportunity to sign up to volunteer Calendar of eventsConnecting MobilizingEndorsement of candidates or party Offline distribution of online materialsComparison of candidates or parties Send link to pageon issues E-paraphernaliaVoter registration information Facilitating statements of public support
  8. 8.  To what extent do political parties and candidates for the 2009 EP elections across the EU differ on these Website- feature dimensions? How can these differences be interpreted in terms of differences in developmental theory and political system characteristics and individual characteristics?Web feature analysisResearch questions
  9. 9.  Human developmental Technological development Political developmentDevelopmental theory
  10. 10.  The more fractionalized a political system is, on average the more Website-features will be utilized. Utilization of Website-features in countries with preferential voting is higher than in countries without preferential voting. To what extent is the general level of trust in political institutions in countries related to the utilization of Website-features? The higher the level of human development, the more Website-features will be utilized. The higher the technological development, the more Website-features will be utilized.Hypotheses
  11. 11.  Party and candidate websites 17 countries Random instead of selective sampling of candidates Empirical validation of scales Multi level analysisimprovements
  12. 12. 4,5 43,5 32,5 21,5 10,5 0 Party Candidate
  13. 13.  Informing Personal Reputation Connecting and Sharing Audio Visualizations
  14. 14. 1,00,90,80,70,60,50,40,30,20,10,0 informing personal info social networking AV supply
  15. 15.  Different types of dimensions of web features Contrary to Norris´ and Foot et al.´s studies ◦ Hardly any country effects
  16. 16. Social media andpolitical communication
  17. 17. New modes of campainging
  18. 18. Premodern campaignsTools Print media, rallies, meetings, foot soldiersMode / style Labor-intensive, interpersonal, amateurOrientation to Mobilizing, voters =voter loyal partisansInternal power Local-centricdistribution
  19. 19. Premodern Modern campaigns campaignsTools Print media, rallies, Broadcast television meetings, foot soldiers news, news advertisements, pollsMode / style Labor-intensive, Capital-intensive, interpersonal, amateur mediated, indirectOrientation to Mobilizing, voters = Converting andvoter loyal partisans mobilizing, voters = loyal partisans and floatingInternal power Local-centric National-centricdistribution
  20. 20. Premodern Modern campaigns Professional campaigns campaignsTools Print media, rallies, Broadcast television Internet, direct mail meetings, foot soldiers news, news advertisements, pollsMode / style Labor-intensive, Capital-intensive, Capital-intensive, interpersonal, amateur mediated, indirect marketed, targeted, continuousOrientation to Mobilizing, voters = Converting and Interactive, voters =voter loyal partisans mobilizing, voters = loyal consumers partisans and floatingInternal power Local-centric National-centric Local-/national centric,distribution bifurcation
  21. 21. Premodern Modern campaigns Professional Personal campaigns campaigns campaignsTools Print media, rallies, Broadcast television Internet, direct mail Weblogs, micro-blogs, meetings, foot soldiers news, news social network sites advertisements, pollsMode / style Labor-intensive, Capital-intensive, Capital-intensive, Low-cost, computer- interpersonal, amateur mediated, indirect marketed, targeted, mediated, networked, continuous personalized, amateurOrientation to Mobilizing, voters = Converting and Interactive, voters = Hyper interactive,voter loyal partisans mobilizing, voters = loyal consumers voters = interested, partisans and floating personalInternal power Local-centric National-centric Local-/national centric, Local-/national-centric,distribution bifurcation individual and networkedBased on Norris and Gibson and Römmele, finsl column by Vergeer, Hermans & Sams
  22. 22.  Many platform - Facebook  Empty platform / - Twitter infrastructure - Linkedin - Facility - Hyves - RenRen - Cyworld - Orkut  User generated content - Youtube - Text - Flickr - Audio - Plurk - Video - Sina Weibo - Pictures - Mixi - EtcSocial media
  23. 23. Social Networking Sites (SNSs)
  24. 24.  Hybrid ◦ Networking  Social  Communicative ◦ Information news provisionTwitter
  25. 25. Number of articles on politics, Internet and social media 180 160 140 120Number of articles 100 80 60 40 20 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Internet and politics (query 1) Social media and politics (query 2) Internet, social media and politics (query 3)Source: Vergeer (in press / 2012) in New Media &
  26. 26. A special case?The Netherlands
  27. 27.  A special case?South Korea
  28. 28.  Extremely wired country ◦ See e.g. Banned from the election campaign ◦ Overruled in court Massively popular Smartphones offered to MPs of the GNPTwitter in South Korea
  29. 29. 2,001,801,601,401,201,000,800,600,400,200,00 rate1 # following for each rate2 # tweets for each rate3 # reciprocal relation rate4 # reciprocal relation follower follower for each follower for each following Korea parliament Korea local elections 2010 Netherlands general elections
  30. 30.  Candidates from parties that do not belong to the establishment have adopted Twitter more frequently and micro-blog more frequently than candidates from parties that belong to the establishment. To what degree is ideology related to candidates’ adoption and micro-blogging activity? The less priority the party has given a candidate, the more likely this candidate adopts and uses Twitter more actively. The more seats a party has lost in the last general elections (external shock), the more likely it is that its candidates use Twitter; Candidates from political parties with uncertain leadership (internal shock) will use micro-blogging more extensively.Hypotheses
  31. 31. • Within Twitter (using the API) • Username • Account creation data • # of followers • And the actual usernames of these followers • # of followers • And the actual usernames of those being followed • Tweet text • And many more (see dev.twitter.com)Data sources
  32. 32.  Tweet ◦ Tweet text ◦ Whether or not it was a reply to another tweet  To whom it was a reply (username/screenname and numerical userid) ◦ Whether or not it was a retweet (according to Twitter)  Which tweet was retweeted (nunerical tweetid)
  33. 33.  Message of tweet Whether or not is was a directed tweet (sent to someone in particular) ◦ Identified by an @-sign Whether or not is was a retweet ◦ Identified by RTType of content
  34. 34.  Undirected tweet ◦ RCMP Commissioner appearing before Public Safety Cmte now. What a popular guy - he has his own paparazzi! Directed tweet ◦ Fantastic blog by my good friend @GlenPearson - http://bit.ly/hlAKXp #lpc Directed tweet to two usernames ◦ @miken32 @CBCEdmonton probably because that is NOT what I said--more commercially viable is different than not needed. Retweet ◦ RT @liberal_party: Think Durham deserves better than Bev Oda? Join @BobRaeMP for a rally tomorrow at 1pm http://lpc.ca/durham #cdnpoli #lpcTweet examples
  35. 35.  Traditional material ◦ Produced by professional actors ◦ Newspapers ◦ Public administration documents Social media ◦ Produced by  professional actors  general publicContent analysis of tweets
  36. 36.  Large quantities of data Word frequencies ◦ Identifying the most important words in the corpus ◦ Code these words into more general categories Switch to SPSS (or other type of data management tool) ◦ Search for the words in the actual tweets ◦ Assign tweet to a specific code Improvements in SPSS ◦ Compute command facilitates many new text operators ◦ Char.index, Char.substr, etc Alternative ◦ Regular expressions ◦ complexData extraction
  37. 37. Communication network
  38. 38.  Total tweets by candidates, followers and followed: ◦ 4,536,854 tweets Breakdown ◦ Tweets among candidates: appr 2% ◦ Tweets to inner circles (followers or being followed) appr 18% ◦ Tweets to outer circle: appr 33% ◦ Tweets not directed to anyone in particular appr 49% ◦ Extracting users from tweets (@adresses)Communication network analysis
  39. 39.  Communication network based on candidates identified in tweets Excluding the general publicCommunication network analysis
  40. 40.  Retrospective ◦ 3200 tweets back in time Cost technical ◦ Access to Firehose for real time dataLimitations in data collection
  41. 41.  Date of tweet ◦ Minute fraction is time stamped with the wrong date Solution ◦ Estimate date and time using the tweetid Status of tweet as retweet ◦ RT Solution:  Use text search operators to identify real retweets (“RT ”, “rt “) Also see http://tinyurl.com/bohhjzn Reply to tweets ◦ Only the first address is identified Solution ◦ Search for multiple @-addresses using text extraction methodsReliability of data as provided bythe API
  42. 42. Thank you for your attention
  43. 43.  Vergeer, M. (accepted for publication/2012). Politics, elections and online campaigning: Past, present ... and a peek into the future. New Media & Society. Hermans, L. & Vergeer, M. (accepted for publication/2012). Personalisation in e- campaigning: Cross-national comparison of personalisation strategies used on candidate websites of 17 countries in EP-elections 2009. New Media & Society. Vergeer, M. & Hermans, L. (accepted for publication/2013). Campaigning on Twitter. Micro- blogging and online social networking as campaign tools in the 2010 general elections in the Netherlands. Journal of Computer-Mediated Communication. Vergeer, M., Hermans, L. & Cunha, C. (accepted for publication/2012). Political parties, candidates, and Web campaigning in the 2009 European Parliament elections. New Media & Society. Vergeer, M., Hermans, L., & Sams, S. (forthcoming). Online social networks and micro- blogging in political campaigning: The exploration of a new campaign tool and a new campaign style. Party Politics. DOI: 10.1177/1354068811407580 Vergeer, M., Eisinga, R. & Franses, Ph.H. (2012). Supply and demand effects in television viewing. A time series analysis. Communications - The European Journal of Communication Research, 37, 79-98. Vergeer, M., Hermans, L., & Sams, S. (2011). Is the voter only a tweet away? Micro- blogging in the 2009 European Parliament elections. First Monday, 16(8).Referenced articles

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