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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Studying online conversations in the Korean blogosphere: A network approach Presentation Transcript

  • 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