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Identifying influential twitter_users

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Identifying influential twitter_users

  1. 1. Chien-leng Hsu (Post-doctoral research fellow)<br />Se Jung Park (PhD student)<br />Han Woo Park (Associate Professor)<br />Department of Media & Communication, WCU Webometrics Institute, Yeungnam University<br />hanpark@ynu.ac.kr http://www.hanpark.net<br />http://english-webometrics.yu.ac.kr<br />Presented at the 5th Complexity Conference, 27 Nov 2010, Seoul, Korea<br />Identifying influential Twitter usersThe case of Sejong City in South Korea<br />
  2. 2. About this study<br />This research explores influential Twitter users and Tweets by:<br />Using Sejong City (세종시) as the case study<br />Using different measurement methods<br />Studying topics (keywords) mentioned in the Tweets<br />
  3. 3. Key Users on Twitter Communities<br />The 2-step flow of communication theory (Katz & Lazarsfeld, 1964)<br />(Online) opinion leaders:<br />determinants of rapid & sustained behaviorchange of members in a community (Valent & Davis, 1999)<br />Park, Jeong & Han (2008)<br />practices (political) participation deligently<br />aggressively expresses opinions<br />
  4. 4. Identifying Key Twitter Users<br />The “network structure” approach:<br /> fails to identify influential Twitter users (Leavitt et al, 2009; Haddadi et al, 2010) <br />The “actor relation” approach:<br />content reachability<br />Fisher & Gilbert (2009) ➭ replies, retweets, mentions & attributions<br />The majority of users: <br />silent & passive<br />a user’s influence: information forwarding activity (Romero et al, in submission)<br />Trace influential user over time<br />
  5. 5. The Sejong City Project<br />The original plan (Moo-Hyun Roh in 2005):<br />To allocate 2/3 of government offices to Sejong, Chungnam (충남)<br />Necessary for regional development<br />The excessive centralization of Seoul & its vicinity➭ limited innovation potential (Shapiro, So & Park, 2010)<br />The revised plan (Myung-Bak Lee):<br />A center for education, scientific research & high-tech industries<br />Partitioning the capital would weaken Korea’s competitiveness & innovation capability<br />
  6. 6. Research Questions<br />Who are the influential users who produce Tweets related to the Sejong City project?<br />What are activities of the influential users?<br />What is the relationship between the influential users?<br />What are the keywords frequently used by the influential users in the Sejong City issue network?<br />
  7. 7. Data collection & analytical techniques<br />Data collection<br />Dates of collection: 15 March ~ 12 April 2010<br />Twitter scraper: An automated computer program to retrieve Tweets from Twtkr (twitterkr.com)<br />Twitter API: Twitter user’s public data<br />Analytical techniques<br />Basic data:<br />Location<br />Number of Tweets<br />Lists of followings<br />Lists of followers<br />Pearson correlation test<br />Four posting activities:<br />Normal tweets<br />Being retweeted by others<br />Being replied by others<br />Being mentioned by others<br />Krkwic (keywords analysis)<br />
  8. 8. (I) Identification of influential users <br />
  9. 9. (II) Twitter activities of the influential users<br />
  10. 10. (III) Relationships between the influential users<br />
  11. 11. (IV) Keywords in the issue network of Sejong City<br />
  12. 12. Amendment of Sejong City law & politicians<br />Critical reviews on Sejong City law<br />Controversies & solutions<br />Agreement & social welfare<br />Other social & political issues<br />Conflicts between political parties<br />Political ideologies & concerns on national debt<br />National policies<br />
  13. 13. Discussions (I)<br />Influential users include media outlets & ordinary users<br />Correlation tests:<br />The occurrence of Tweets vs. the number of Tweets ➭ significantly correlated (Pearson correlation=0.663, p<.01)➭ Influential users tended to address public issues<br />The number of followers vs. the number of followings➭ significantly correlated (Pearson correlation=0.871, p<.01)➭ Influential users had mutual ties in the network<br />Influential users are likely to act as news brokers & deliver their views in a single-issue community<br />Having mutual relations with other influential users may allow an influetial user to make his/her own opinions available to a wider audience<br />
  14. 14. Discussions (II)<br />Referral activities/relationships<br />Media outlets ➭ normal tweets ➭ messages were not circulated well among other users<br />Ordinary users<br />normal tweets, retweets, mentions & replies <br />More likely to interact with the indirect presence of media outlets<br />Keyword network<br />Politicians, government projects & social-political issues mentioned<br />Influential user <br />some keywords specific to his/her cluster<br />similar keywords used ➭ a sense of community <br />
  15. 15. Thank you.<br />

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