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<ul>Studying online conversations  in the Korean blogosphere: A network approach </ul>Anatoliy Gruzd  ( [email_address] ) ...
<ul>What content-based features of online interactions help to uncover nodes and ties between online participants? </ul><u...
<ul>ICTA - Online Tool for Social Network Discovery  http://TextAnalytics.net </ul>
Objectives <ul><li>Automated analysis of online interactions and conversations in the Korean blogosphere
Develop and evaluate an e-research tool called the Korean Internet Network Miner (KINM) </li></ul>
Dataset <ul><li>OhMyNews – popular blogging website in Korea
Single blog authored by  방짜  (bangzza)  http://blog.ohmynews.com/bangzza
~1,000 comments (April 2008 - April 2009) </li></ul>
Sample blog post and comments
Automated Discovery of Social Networks Chain (reply-to) method Visualized by CMU ORA
<ul>Automated Discovery of Social Networks    Name Network   Approach </ul><ul>Method </ul><ul>Connect the sender to peopl...
<ul><li>Main Communicative Functions of Personal Names (Leech, 1999)   </li></ul><ul><ul><li>getting attention and identif...
maintaining and reinforcing social relationship s </li></ul></ul><ul><li>Names are “one of the few textual carriers of ide...
Their use is crucial for the creation and maintenance of a sense of community (Ubon, 2005) </li></ul><ul>Automated Discove...
Network representation of blog comments
Semi-automated network evaluation <ul>1   난  (I)  2   사진쟁이  (Photographer)  3   그래서  (and, so) 4   테츠  (Tetz) 5   방짜  (Ban...
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Studying online conversations in the Korean blogosphere: A network approach

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Studying online conversations in the Korean blogosphere: A network approach

  1. 1. <ul>Studying online conversations in the Korean blogosphere: A network approach </ul>Anatoliy Gruzd ( [email_address] ) <ul><li>Dalhousie University, Canada </li></ul>Chung Joo Chung ( [email_address] ) <ul><li>State University of New York at Buffalo, USA </li></ul>Han Woo PARK ( [email_address] ) <ul><li>YeungNam University, Korea </li></ul>International Sunbelt Social Network Conference Riva del Garda, Italy July 3, 2010
  2. 2. <ul>What content-based features of online interactions help to uncover nodes and ties between online participants? </ul><ul>Automated Discovery of Social Networks among Blog Readers/Commentators </ul><ul>? </ul>
  3. 3. <ul>ICTA - Online Tool for Social Network Discovery http://TextAnalytics.net </ul>
  4. 4. Objectives <ul><li>Automated analysis of online interactions and conversations in the Korean blogosphere
  5. 5. Develop and evaluate an e-research tool called the Korean Internet Network Miner (KINM) </li></ul>
  6. 6. Dataset <ul><li>OhMyNews – popular blogging website in Korea
  7. 7. Single blog authored by 방짜 (bangzza) http://blog.ohmynews.com/bangzza
  8. 8. ~1,000 comments (April 2008 - April 2009) </li></ul>
  9. 9. Sample blog post and comments
  10. 10. Automated Discovery of Social Networks Chain (reply-to) method Visualized by CMU ORA
  11. 11. <ul>Automated Discovery of Social Networks Name Network Approach </ul><ul>Method </ul><ul>Connect the sender to people mentioned in the message </ul><ul>Connect people whose names co-occur in the same message(s) </ul><ul>Discovered Tie(s) </ul><ul>Ann -> Steve Ann -> Natasha </ul><ul>Steve <-> Natasha </ul><ul>FROM: Ann “ Steve and Natasha , I couldn't wait to see your site. I knew it was going to [be] awesome!” </ul><ul>This approach looks for personal names in the content of the comments to identify social connections between online participants. </ul>
  12. 12. <ul><li>Main Communicative Functions of Personal Names (Leech, 1999) </li></ul><ul><ul><li>getting attention and identifying addressee
  13. 13. maintaining and reinforcing social relationship s </li></ul></ul><ul><li>Names are “one of the few textual carriers of identity” in discussions on the web (Doherty, 2004)
  14. 14. Their use is crucial for the creation and maintenance of a sense of community (Ubon, 2005) </li></ul><ul>Automated Discovery of Social Networks Name Network Approach </ul>
  15. 15. Network representation of blog comments
  16. 16. Semi-automated network evaluation <ul>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) </ul><ul>Among 10 nodes, only 2 , 4 , 5 and 7 are NANEs or IDs of participants in the Bangzza blog </ul><ul>1 </ul><ul>2 </ul><ul>3 </ul><ul>5 </ul><ul>6 </ul><ul>7 </ul><ul>10 </ul><ul>8 </ul><ul>9 </ul><ul>4 </ul>
  17. 17. Clues suggesting that a word is likely to be a nickname <ul><li>context words such as &quot; 님 &quot; = an honorific or &quot; 씨 &quot; = Mr./Ms
  18. 18. full name, which is almost always three characters
  19. 19. punctuation indicative of someone being addressed (e.g., “/” or “:”)
  20. 20. combination of characters (Korean, English and/or Chinese), symbols (e.g., underscores, hyphens) and numbers
  21. 21. patterns indicative of non-native words </li><ul><li>phonetic koreanization of English (e.g., &quot; 미디어몽골 &quot; = mediamogul = Media Mogul)
  22. 22. phonetic romanization of Korean (e.g. “jihwaja” = 지화자 ) </li></ul></ul>
  23. 23. Words that are NOT likely to be used as a nickname <ul><li>a word candidate is a phrase </li><ul><li>e.g., if the “FROM” field is used more like a subject line (possible indicators include white spaces and length) </li></ul><li>a word candidate consists of a single character (e.g., “a” or “ ㄱ ” )
  24. 24. a word candidate consists of netspeak </li><ul><li>emoticons (e.g. “=_=”)
  25. 25. slang and abbreviations (e.g., using “2MB” to refer to the former Korean president)
  26. 26. onomatopoeia (e.g., &quot; ㅋㅋ ” = heehee, &quot; 하하 ” = haha) </li></ul></ul>
  27. 27. Words that are NOT likely to be used as a nickname (2) <ul><li>a word candidate appears more than one time in the comment
  28. 28. a word candidate consists of random characters (e.g. &quot; ㅁㄴㅇㄹ &quot; or “asdf”)
  29. 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. 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) </li></ul>
  31. 31. Conclusion <ul><li>A network representation of comments posted to a blog makes it much easier to analyze social interactions among online participants
  32. 32. Even in a blog dominated by mostly anonymous and argumentative commentators, a community can still emerge
  33. 33. Suggested future improvements to our network discovery algorithm. </li></ul>
  34. 34. Acknowledgments <ul><li>Jaeeun Yoo at the University of Toronto for her help with the data analysis
  35. 35. The project is in part supported by </li></ul>

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