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Twitter as an Imagined Community

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A Case Study of Barry Wellman’s Twitter network

A Case Study of Barry Wellman’s Twitter network

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    Twitter as an Imagined Community Twitter as an Imagined Community Presentation Transcript

    • A Tweetise on Twitter as an Imagined Community A Case Study of Barry Wellman’s Twitter network Anatoliy Gruzd Information Management Dalhousie Univ ersity Barry Wellman Sociology, NetLab University of Toronto Yuri Takhteyev iSchool University of Toronto International Sunbelt Social Network Conference Riva del Garda, Italy July 2, 2010
    • The Triple Revolution
      • 1. Social Networks
        • From bounded solidary comprehensive groups
        • To unbounded , sparsely-knit, fragmented nets
        • Started before the Internet
      • Multiple partial networks afford greater expansion of time, space, extensibility, partitions
        • Permeable boundaries
        • Flatter, more complex hierarchies
        • Individuals switch among multiple, overlapping nets
    • Add the Internet & Wireless
      • 2. Personal Internet
        • Loosely bounded
        • Personal ICT appliance – unlike phone, family encyclopedia
        • Online & offline intertwined
      • 3. Mobile Access & Availability (also Personal)
        • You can access people & info anywhere 
        • You are available to them (:
        • Online & offline even more intertwined
      • Facilitates Durkheimian “Mechanical Solidarity”
    • Lee Rainie & Barry Wellman
      • Networked – The New Social Operating System
      • MIT Press, Fall 2011
      • Lee is Director of the Pew Internet & American Life project
    • Specialized Forms of Communication: Helps Build Imagined (Personal) Community
      • Benedict Anderson, Imagined Communities (1983)
      • Public-Private – Overlapping Personal communities
      • Few hide under aliases: mini-bios available
      • 140 character constraint  abbrevs, syntax
      • Language: concise, direct; no passive voice
    • Barry’s Twitter Home Page, August 2, 10am
    • I Am, Therefore I Tweet
      • Started on Twitter March 2009
        • Objective: spread news of my work
        • Group alerts to discussions elsewhere @ Social Network Conference
      • These Data are for August 2009: larger now
      • Tweeted 1,000+ Times
        • One-quarter have been ReTweets (RT)
      • I “Follow” 114 peeps – “Sources” (our term)
        • Twitter calls them “Friends” – even more misleading than Facebook
        • 61 (53%) of whom I Follow, Follow me: “Mutuals” (our term)
        • 418 mutual ties among these 61 Mutuals (mean =7.0)
          • Network density =0.12
      • 794 are “Followers”
        • 61 Mutuals + 592 who only Follow Me (but I don’t follow)
      • Source/Follower ratio = 1 : 5.8
        • Nearly 6x as many people Follow me as I Follow
        • Asymmetric status – a prominence measure
    • Barry Tweets for His Sources
      • Know about them: 138, not 794
      • Especially, the Mutuals who have dialogue
      • And hope others (mostly strangers) get something useful
        • Avoid inside jokes (mostly)
      • Mutuals get disproportionate mindshare/time
        • Online & in my life
        • Mostly ICT mavens
        • Shared language, understanding, knowledge, community
        • Scants other parts of Barry’s life: social network, community studies, kin & friends, wife
    • Three Degrees of Possible ReTweeting
      • 2 nd Degree:
        • Barry`s 114 Sources have 15,502 Followers mean=136
        • All with professional needs to scan & retransmit info
      • Sources’ Sources = 2,662,821 unique names
        • If only many/most ReTweeted !
      • More tweets & retweets  more visibility  more followers (until you overwhelm)
    • Why Do I Tweet & ReTweet?
      • Tweet
        • To get my ideas out
        • Promote my writing
        • Share deep & fun thoughts
        • Share important experiences (Grand Canyon raft)
        • Comment on others: 24.7% of my tweets are replies, comments @someone
        • Reproduce important bits of a conference: schmooze, news
        • Or if you like: literary salon, cocktail party
      • ReTweet (26.9% of my recent tweets)
        • Get friends’ good ideas out
        • Promote their work
        • Build networks thru reciprocity
        • Hero worship
        • Kissing butt (will X notice I’ve RT’d her?)
    • Why Do Tweeps Follow?
      • Want to Know What Friends, Strangers are Doing (THE_REAL_SHAQ)
        • Brushes with Celebrities: Like a Fan Zine
        • Ashton Kutcher has 3,021,363 Followers
          • He Follows 190
      • Early Adopters – want to be on the newest thing
      • Want to Learn from Others
        • Directly
        • Thru Pointers to Other Web Sites
        • News Services (CNN, NYT all Tweet)
      • Referrals from Others
        • Ester (Hargittai): I call it the @zephoria bump: wake up w/a bunch of new followers, danah (boyd) must've tweeted something
      • AutoFollow: If I follow you, you’ll follow me
        • Content specialists, using automatic software
          • Ex: Mentioned Las Vegas & tourist office Followed
        • Marketers: Dredging lists. Some buy lists of 5,000
    • Variable Sense of Community
      • Twitter updates feel like whispering into the wind
        • “ Everyone’s out there to rack up numbers.” – Melinda Blau
      • I carry on a dialogue with about 20 Mutuals
      • + about 20 non-Mutual Followers who have responded to me @Barrywellman
      • Do others even read or is it like collecting autographs?
      • Is there a sense of community ?
      • Over to Anatoliy >>>>>
    • Characteristics of Online Community
      • Anderson’s imagined communities (1983)
        • Common language
        • Temporality
        • “ High Centers”
      • Jones` Virtual Settlement (1997)
        • virtual common-public-place
        • interactivity
        • sustained membership
      • McMillan & Chavis` Sense of Community (1986)
        • feelings of membership & influence
        • reinforcement of needs
        • shared emotional connection
      • Rainie & Wellman’s new book
    • Dataset 1) August 2009 - 56 mutuals, 140 connections 2) February 2010 - 72 mutuals, 285 connections 3) April 2009 - February 2010 - 3,112 tweets
    • Twitterspeak : Specialized Language & Norms For all Twitter users: URL shorteners to save space: bit.ly Hashtags (#): #Sunbelt RT (ReTweet) @name (@dalprof) ------------------------------- For Barry`s network: “ Wellman:” or “Me:” “ ( X of Y)” or “(X/Y)”
    • “ High Centers”
      • An “imagined” community on Twitter is dual-faceted - collective and personal
      • The collective Twitter community forms around high centers who are popular individuals (danah boyd), celebrities (Britney), or organizations such as media companies (BBC)
      • The high centers in the personal Twitter don't have to be “celebrities”, but
      • The local and overall high centers overlap to some extent
    • Interactivity
      • 60% of Barry's tweets included the @ sign
        • The average Twitter user – 24.5% (Huberman et al, 2009), 12.5% (Java et al., 2006)
      • “ Name network” (co-occurrence of usernames)
        • 3,112 tweets-> 512 users(1,448 ties) vs. 56 mutuals(101 ties)
        • Result: The mutual network of 56 users is 6 times denser than the larger interaction network of 512 users
      • QAP correlation of 0.27 (p<0.05) between the mutual and interaction networks.
    • “ Auto” Clusters in Barry’s Twitter Network Organizational Pew Human Computer Interaction Soc Net Analysis/ Toronto Internet & Society A Very Biased Map of my Overall Net: Hi on ICT; No Kin; Few Sociologists Newman clustering
    • “ Manual” Clusters in Barry’s Twitter Network
    • Summary (1)
      • Barry`s network exhibits characteristics of
      • Anderson’s “imagined communities”
      • Jones’ “virtual settlement”
      • McMillan and Chavis’ “sense of community”
      • Wellman’s “networked individualism”
      • Barry`s network is both “real” and “ imagined ”
        • real because the participants interact, especially the mutuals
        • imagined because they have some sense of community
    • Summary (2)
      • Why Barry’s online community has grown while maintaining a sense of community?
        • Core members who actively interact with each other & participate in the community for a long time
        • Barry's community is open to newcomers
          • Twitter’s asynchronous connections
          • Trust, professionalism and informality among the active mutuals
        • Combo of strong & weak ties  connectivity between social circles
    • Full paper available @ www.chass.utoronto.ca/~wellman Anatoliy Gruzd Yuri Takhteyev
        • Anatoliy Gruzd, Barry Wellman & Yuri Takhteyev
        • “ Twitter as an Imagined Community”
        • American Behavioral Scientist 54, 2011
        • Special Issue on Imagined Communities