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Studying online conversations in the Korean blogosphere: A network approach

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  • This work is supported by SSHRC on the Canadian side and by the World University project on the Korean side.
  • .
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    • 1.
        Studying online conversations in the Korean blogosphere: A network approach
      Anatoliy Gruzd ( [email_address] )
      • Dalhousie University, Canada
      Chung Joo Chung ( [email_address] )
      • State University of New York at Buffalo, USA
      Han Woo PARK ( [email_address] )
      • YeungNam University, Korea
      International Sunbelt Social Network Conference Riva del Garda, Italy July 3, 2010
    • 2.
        What content-based features of online interactions help to uncover nodes and ties between online participants?
        Automated Discovery of Social Networks among Blog Readers/Commentators
        ?
    • 3.
        ICTA - Online Tool for Social Network Discovery http://TextAnalytics.net
    • 4. Objectives
      • Automated analysis of online interactions and conversations in the Korean blogosphere
      • 5. Develop and evaluate an e-research tool called the Korean Internet Network Miner (KINM)
    • 6. Dataset
      • OhMyNews – popular blogging website in Korea
      • 7. Single blog authored by 방짜 (bangzza) http://blog.ohmynews.com/bangzza
      • 8. ~1,000 comments (April 2008 - April 2009)
    • 9. Sample blog post and comments
    • 10. Automated Discovery of Social Networks Chain (reply-to) method Visualized by CMU ORA
    • 11.
        Automated Discovery of Social Networks Name Network Approach
        Method
        Connect the sender to people mentioned in the message
        Connect people whose names co-occur in the same message(s)
        Discovered Tie(s)
        Ann -> Steve Ann -> Natasha
        Steve <-> Natasha
        FROM: Ann “ Steve and Natasha , I couldn't wait to see your site. I knew it was going to [be] awesome!”
        This approach looks for personal names in the content of the comments to identify social connections between online participants.
    • 12.
      • Main Communicative Functions of Personal Names (Leech, 1999)
        • getting attention and identifying addressee
        • 13. maintaining and reinforcing social relationship s
      • Names are “one of the few textual carriers of identity” in discussions on the web (Doherty, 2004)
      • 14. Their use is crucial for the creation and maintenance of a sense of community (Ubon, 2005)
        Automated Discovery of Social Networks Name Network Approach
    • 15. Network representation of blog comments
    • 16. Semi-automated network evaluation
        1 난 (I) 2 사진쟁이 (Photographer) 3 그래서 (and, so) 4 테츠 (Tetz) 5 방짜 (Bangzza) 6 댓글 (comment) 7 녹두 (Nokdu) 8 ㅋㅋ (  , : )) 9 좀 (a little, a bit) 10 사람 (people)
        Among 10 nodes, only 2 , 4 , 5 and 7 are NANEs or IDs of participants in the Bangzza blog
        1
        2
        3
        5
        6
        7
        10
        8
        9
        4
    • 17. Clues suggesting that a word is likely to be a nickname
      • context words such as &quot; 님 &quot; = an honorific or &quot; 씨 &quot; = Mr./Ms
      • 18. full name, which is almost always three characters
      • 19. punctuation indicative of someone being addressed (e.g., “/” or “:”)
      • 20. combination of characters (Korean, English and/or Chinese), symbols (e.g., underscores, hyphens) and numbers
      • 21. patterns indicative of non-native words
        • phonetic koreanization of English (e.g., &quot; 미디어몽골 &quot; = mediamogul = Media Mogul)
        • 22. phonetic romanization of Korean (e.g. “jihwaja” = 지화자 )
    • 23. Words that are NOT likely to be used as a nickname
      • a word candidate is a phrase
        • e.g., if the “FROM” field is used more like a subject line (possible indicators include white spaces and length)
      • a word candidate consists of a single character (e.g., “a” or “ ㄱ ” )
      • 24. a word candidate consists of netspeak
        • emoticons (e.g. “=_=”)
        • 25. slang and abbreviations (e.g., using “2MB” to refer to the former Korean president)
        • 26. onomatopoeia (e.g., &quot; ㅋㅋ ” = heehee, &quot; 하하 ” = haha)
    • 27. Words that are NOT likely to be used as a nickname (2)
      • a word candidate appears more than one time in the comment
      • 28. a word candidate consists of random characters (e.g. &quot; ㅁㄴㅇㄹ &quot; or “asdf”)
      • 29. a word candidate is a short, conversational word or phrase (e.g., &quot; 나 &quot; = me,&quot; 아이고 &quot; = oh no, &quot; 그래서 &quot; = so/therefore)
      • 30. a word candidate is a common word or idea in the given context/topic (e.g &quot; 대한민국 &quot; = Republic of Korea, &quot; 쥐체사상 &quot; = a newly created word used to refer to political fanatics)
    • 31. Conclusion
      • A network representation of comments posted to a blog makes it much easier to analyze social interactions among online participants
      • 32. Even in a blog dominated by mostly anonymous and argumentative commentators, a community can still emerge
      • 33. Suggested future improvements to our network discovery algorithm.
    • 34. Acknowledgments
      • Jaeeun Yoo at the University of Toronto for her help with the data analysis
      • 35. The project is in part supported by