3. Webometrics in terms of e-research A minor but growing approach to the study of Internet-mediated communication A new methodological perspective based on the use of new digital tools available online for conducting humanities and social science Internet research

5. http://participatorysociety.org/wiki/index.php?title=Online_Research

6. Web Scrapers, Crawlers, Tools in WCU

11. Component of Naver WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICSS WITH E-RESEARCH TOOLS WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICSS WITH E-RESEARCH TOOLS Log-in The articles title (changing automatically ) The press linked Today’s issues Quick menu browser window

12. Naver search options

14. http://english-webometrics.yu.ac.kr/WebometricsTools/WeboNaver/WeboNaver.html

18. Monitoring a Socio-political Blogosphere in South Korea: Comparing a Metrics from Blogosphere with Voter Turnout

22. Constituency Candidate Blog % Rank Vote % Rank Jangan, Suwon, Gyeonggi Park, CS( 박찬숙 ) 213.4 35.6 2 33,106 42.7 2 Lee, CY( 이찬열 ) 216.6 36.1 1 38,187 49.2 1 Ahn, DS( 안동섭 ) 158.4 26.4 3 5,570 7.2 3 Yoon, JY( 윤준영 ) 11.8 2.0 4 716 0.9 4 Sangrok-B, Ansan, Gyeonggi Song, JS( 송진섭 ) 147.8 17.0 3 11,420 33.2 2 Kim, YH( 김영환 ) 280.1 32.3 1 14,176 41.2 1 Jang, KW( 장경우 ) 64.0 7.4 4 1,145 3.3 4 Kim, SK( 김석균 ) 25.7 3.0 6 896 2.6 6 Yoon, MW( 윤문원 ) 22.8 2.6 7 439 1.3 7 Lee, YH( 이영호 ) 59.5 6.9 5 987 2.9 5 Lim, JI( 임종인 ) 268.6 30.9 2 5,363 15.6 3 Gangreung, Gangwon Kwon, SD( 권성동 ) 85.6 32.9 1 29,010 50.9 1 Hong, JK( 홍재경 ) 68.0 26.1 3 2,100 3.7 4 Song, YC( 송영철 ) 72.1 27.7 2 19,867 34.8 2 Shim, KS( 심기섭 ) 34.9 13.4 4 6,054 10.6 3 North Chungcheong (4 districts) Kyoung, DS( 경대수 ) 140.2 25.2 2 19,427 28.4 2 Chung, BG( 정범구 ) 167.1 30.0 1 29,120 42.5 1 Chung, WH( 정원헌 ) 65.2 11.7 5 3,071 4.5 4 Park, KS( 박기수 ) 68.8 12.4 4 2,125 3.1 5 Lee, TH( 이태희 ) 33.2 6.0 6 504 0.7 6 Kim, KH( 김경회 ) 81.7 14.7 3 14,218 20.8 3 Yangsan, South Gyungsang Park, HT( 박희태 ) 258.2 30.4 1 16,597 37.9 1 Song, IB( 송인배 ) 214.2 25.2 2 15,577 35.6 2 Park, SH( 박승흡 ) 134.0 15.8 3 1,550 3.5 5 Kim, SG( 김상걸 ) 33.4 3.9 6 900 2.1 6 Kim, YS( 김양수 ) 88.7 10.5 4 5,875 13.4 3 Kim, YK( 김용구 ) 26.6 3.1 8 234 0.5 8 Kim, JM( 김진명 ) 29.3 3.5 7 325 0.7 7 Yoo, JM( 유재명 ) 64.3 7.6 5 2,710 6.2 4

26. Cyworld Extractor - Overview Java-based software tool that, given the URL of a politician on Cyworld, extracts comments given by citizens along with related profile attributes. The stored data, which can amount to thousands of records, is stored in a suitable format for import into statistical software

27. ① ② ③ The status of mini-homepy ① How active ②How famous ③How friendly Gender Name Geun-Hye Park’s mini-hompy Visitor count

30. South Koreans fearing 'mad cow disease' fight US beef imports in May and June 2008

33. IP address Cyworld-IP screen capture Seong-Min Yoo’s mini-hompy

34. Cyworld Extractor – Data One example of possible uses for the collected data is to determine the region of posters commenting from Korea

35. Cyworld Extractor - Data The country of origin of those users commenting from outside Korea is also possible

36. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS Case 2. Cyworld Mini-hompies of Korean Legislators Cyworld Mini-hompies of Korean legislators: Co-inlink network map using Yahoo.com However, buddy data is not publicly available!! The network structure using co-link data shows a clear butterfly pattern. T here is one hub (ghism) that belongs to Park Gy un-Hye (Park GH, www.cyworld.com/ghism), the daughter of ex-president Park Jeong-Hee and one of two major GNP candidates (along with president-elect Lee MB) in the 2007 presidential race.

38. Facebook

40. Screen capture of Plurk

41. Research examples on Plurk

44. Twitter Extractor - Overview Sharing a similar interface and extraction mechanism with the Cyworld extractor, this application requires the URL of a user on Twitter. It is then possible to collect all tweets and determine the attributes of the user’s follower / following network

45. Twitter Extractor - Data A simple use for this data would be to visualize a user’s network and ascertain which users are reciprocal in their friendships

46. * A type of tweets - A case Study on twitter of 18th National Assembly Members * Audiences of tweets * Topic of tweets

47. Twtkr.com Scraper

48. Korean Internet Network Miner: A Korean version of ICTA

52. Section 2. Evaluation of the Name Network Discovery Algorithm The second set includes clues suggesting that a word is NOT likely to be used as a nickname : ● a word candidate is a phrase—for example, if the nickname input (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 "); ● a word candidate consists of netspeak, including emoticons(e.g. "=_="), slang and abbreviations(e.g., using "2MB" to refer to the current Korean president), and onomatopoeia (e.g. " ㅉㅉ " = tsk tsk, ” ㅋㅋ " = heehee, " 하하 " = haha, " 음 " = hmm); ● a word candidate appears more than one time in the comment; ● a word candidate consists of random characters(e.g. " ㅁㄴㅇㄹ " or "asdf"); ● a word candidate is a short, conversational word or phrase(e.g., " 나나 " = me, " 아이고 " = oh no, " 그래서 " = so/therefore); ● a word candidate is a common word or idea in the given context/topic(e.g., " 대한민국 " = Republic of Korea, " 쥐체사상 " = a newly created word used to refer to political fanatics).

61. Web Type Year Sum of links (Mean) Density Centralisation Gini Coefficient In Out Web 1.0 (N=245) 2000 373 (1.52) 0.006 1.84 69.33 0.984 2001 515 (2.10) 0.009 1.19 99.55 0.996 Web 2.0 (N=99) 2005 652 (6.59) 0.067 22.07 41.66 0.759 2006 589 (5.95) 0.061 20.67 35.10 0.763 Twitter (N=22) 2009 111 (5.05) 0.240 24.72 39.68 0.408

64. Incoming International Hyperlink in 2009 (drawn using ManyEyes.com)

65. Incoming International Hyperlink in 2009 (drawn using Google Earth)

66. Thank you for listening! WCU WEBOMETRICS INSTITUTE Acknowledgments. WCU Webometrics Institute acknowledges that this research is supported from the WCU project investigating internet-based politics using e-research tools granted from South Korean Government