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Overview Of Wcu Research (16 Dec2009)Sj
1. Investigating Internet-based Korean politics using e-research tools Prof. Han Woo PARK Associate Professor Dept. of Media & Communication, YeungNamUniversity 214-1 Dae-dong, Gyeongsan-si,Gyeongsangbuk-do 712-749, S.Korea [email_address] http://www.hanpark.net Director of WCU Webometrics Institute http://english-webometrics.yu.ac.kr This is in collaboration with Dr. Yon-Soo Lim, Dr. Chieng-Leng Hsu, DPhil. Steven Sams, DPhil, Se-Jung Park, and Ting Wang. Many thanks to my colleagues and assistants!! WCU WEBOMETRICS INSTITUTE
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3. How is different from e-science, e-humanities, e-social science? What is e-research ? What is current status of e-research in South Korea?
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5. What is e-research? A minor but growing approach to the study of e-science is the methodological perspective based on the use of new digital tools available online for conducting humanities and social science research. While the first two strands are closely associated with the natural and engineering science community, the third approach is less connected to that community and more associated with the broader interdisciplinary research community .
8. <Table 1> Development stage of e-Science Nentwich(2003) Type Traditional Science -------------------------> e-Science Stage 1 2 3 4 Information gathering Libraries; personal conversations Offline database Online databases; link collections; discussion lists Digital libraries; Knowbots Data production Interviews; experiments Electron, text analysis; simulation/ modeling Internet surveys Distributed computing; virtual reality Data management Card files; lists Hypertextual card files; databases Networked card files; de-central databases Data processing/ analysis With paper and pencil Electron, data-processing; expert systems Modelling; simulations Artificial intelligence
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12. WCUBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS Empirical findings on current status of e-research in South Korea - Search queries and returned webpages and websites Korean English webpages found webpages returned sites 사이버인프라 C yberinfrastructure 8,210 296 230 사이버연구 C yberresearch 65,900 285 219 디지털인문학 digital humanities 12,300 164 128 E - 사이언스 E -science 17,000 199 142 사이버과학연구 C yberscience 58 43 35 E - 인프라 E -infrastructure 98 39 35 E - 리서치 E -research 102 28 20 E - 인문학 E -humanities 1 1 1 E - 사회과학 E -social science 0 0 0 Total 103,709 1,055 810
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16. Author types of Korea e-science websites WCU WEBOMETRICS INSTITUTE Media sites were the most frequently retrieved, with slightly less than half of the sites for this study (44 out of 104 sites) Author types No. of sites Percent Mass media 27 26.0 Public/Government 18 17.3 Technology Media 17 16.3 Portals/Search engines/Blogs 15 14.4 Private/Industry 14 13.5 Academic/University 13 12.5 Total 104 100.0
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20. Korea’s politicized cyberspace Core-peripheral structure of diffusion Similar to ‘Slash dot effect’ in the US, web-based discussion media have been playing a tremendous role in raising public awareness and providing an investigative reporting abut US beef
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26. Theoretical controversy of Balkanization Unjustified temporal effect: Some negative evidences about deepening divide Simplified media usage model: Shifting from DailyMe to Produsage Limited to political cooperation issues in a well-connected social world: ‘ Collective intelligence ’ certainly occurs in some (loose) contexts
27. Theoretical controversy of Mobilization Several factors involved: Socio-political-cultural constraints and practices (e.g., regulation, policing, IT infra, power-distance etc.) Inter-media agenda setting: Influential conventional media’s impact on users Competitive media market: Obsolete DailyMe Increasing media education: Multiple site-browsing and balanced approach
28. Axel Brun’s produsage is defined as "the collaborative and continuous building and extending of existing content in pursuit of further improvement" , but that's only the starting point. Again, it's important to note that the processes of produsage are often massively distributed, and not all participants are even aware of their contribution to produsage projects; their motivations may be mainly social or individual, and still their acts of participation can be harnessed as contributions to produsage
40. 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
48. Cyworld Extractor – Data One example of possible uses for the collected data is to determine the region of posters commenting from Korea
49. Cyworld Extractor - Data The country of origin of those users commenting from outside Korea is also possible
50. 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
51. 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
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55. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITIC WITH E-RESEARCH TOOLS Background information of 18 th Korean MPs Gender Age Type Male Female 30-39 40-49 50-59 60-69 70-79 Frequency (%) 251 (86.0%) 41 (14.0%) 3 (1.0%) 52 (17.8%) 144 (49.3%) 80 (27.4%) 13 (4.5%) The number of terms (how many times he/she has been elected for the national assembly) Term 1th 2th 3th 4th 5th 6th 7th Frequency (%) 130 (44.5%) 89 (30.5%) 44 (15.1%) 19 (6.5%) 6 (2.1%) 3 (1.0%) 1 (0.3%) Party Frequency (%) Constituency Classification Frequency (%) Grand National Party 168(57.5%) Seoul and its vicinity -Seoul, Incheon, Gyeonggi-do 110(37.7%) Democratic Labor Party 5(1.7%) Provincial regions -Daejeon, Ulsan, Gwangju, Busan, Daegu, Gangwon-do, Chungcheongnam/buk-do, Gyeongshangnam/buk-do, Jeollanam/buk-do, Jeju-do 131(44.9%) Democratic Party 84(28.8%) Liberty Forward Party 18(6.2%) Pro-Park Geun-hye Coalition 5(1.7%) Renewal of Korea Party 3(1.0%) Proportional representation 51(17.5%) New Progressive Party 1(.3%) Independent 8(2.7%)
60. Captured on 19th June, 2009 * Female: Red , Male: Blue , Ruling party: italic Cyworld presence of Korean politicians Cyworld Comments Visitor counts Bookmarked by Others Scraped Posting Submission Date Active Score Famous Score Friendly Score Kyoeng-Won Na Geun-Hye Park Geun-Hye Park Geun-Hye Park Sung-Tae Kim Geun-Hye Park Geun-Hye Park Geun-Hye Park Geun-Hye Park Hoi-Chang Lee Jung-Wook Hong Guk-Hyun Moon Ju-Young Lee Kyoeng-Won Na Kyoeng-Won Na Guk-Hyun Moon Hoi-Chang Lee Kyung-Won Na Guk-Hyun Moon Jung-Wook Hong Jin Park Dong-Yong Chung Dong-Young Jung Dong-Young Jung Kyeong-Tae Jo Dong-Young Jung Dong-Young Jung Hoi-Chang Lee Heung-Gil Ko Soo-hee Jin Guk-Hyun Moon Kyoeng-Won Na Dong-Yong Chung Guk-Hyun Moon Kyoeng-Won Na Dong-Yong Chung Geun-Hye Park Hee-Ryong Won Woon-Tae Kang Gi-Gab Kang Kook-Hyn Moon Jung-Wook Hong Hoi-Chang Lee Kyoeng-Won Na Dong-Young Jung Hong-jun An Kyung-Tae Cho Hee-Ryong Won Gi-Gab Kang Woon-Tae Kang Hee-Ryong Won Eul-Dong Kim Seok-Yong Yoon Jin-ha Hwang Hee-Ryong Won Mong-Jun Chung Sook-Mi Son Kyung-Tae Cho Mong-Jun Chung Sun-Kyo Han Jae-Chul Sim Jae-chul Sim Eul-Dong Kim Jae-chul Sim Mong-Jun Chung Hee-Ryong Won Eul-Dong Kim Mong-Jun Chung Woo-Yeo Hwang Woon-tae Kang Mong-Jun Chung Sun-Kyo Han Jeong-Wook Hong Eul-Dong Kim Sun-Kyo Han Gi-Gab Kang Jin-Pyo Kim Sun-Kyo Han Jun-pyo Hong Jun-pyo Hong
61. Captured on 19th June, 2009 * Female: Red , Male: Blue , Ruling party: italic Cyworld presence of Korean politicians Cyworld Comments Visitor counts Bookmarked by Others Scraped Posting Active Score Famous Score Friendly Score Kyoeng-Won Na Geun-Hye Park Geun-Hye Park Geun-Hye Park Geun-Hye Park Geun-Hye Park Geun-Hye Park Geun-Hye Park Hoi-Chang Lee Jung-Wook Hong Guk-Hyun Moon Kyoeng-Won Na Kyoeng-Won Na Guk-Hyun Moon Hoi-Chang Lee Kyung-Won Na Guk-Hyun Moon Jung-Wook Hong Dong-Yong Chung Dong-Young Jung Dong-Young Jung Kyeong-Tae Jo Dong-Young Jung Dong-Young Jung Hoi-Chang Lee Soo-hee Jin Guk-Hyun Moon Kyoeng-Won Na Dong-Yong Chung Guk-Hyun Moon Kyoeng-Won Na Dong-Yong Chung Hee-Ryong Won Woon-Tae Kang Gi-Gab Kang Kook-Hyn Moon Jung-Wook Hong Hoi-Chang Lee Kyoeng-Won Na Hong-jun An Kyung-Tae Cho Hee-Ryong Won Gi-Gab Kang Woon-Tae Kang Hee-Ryong Won Eul-Dong Kim Jin-ha Hwang Hee-Ryong Won Mong-Jun Chung Sook-Mi Son Kyung-Tae Cho Mong-Jun Chung Sun-Kyo Han Jae-chul Sim Eul-Dong Kim Jae-chul Sim Mong-Jun Chung Hee-Ryong Won Eul-Dong Kim Mong-Jun Chung Woon-tae Kang Mong-Jun Chung Sun-Kyo Han Jeong-Wook Hong Eul-Dong Kim Sun-Kyo Han Gi-Gab Kang Sun-Kyo Han Jun-pyo Hong Jun-pyo Hong
64. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS Case 2. Cyworld Mini-hompies of Korean Legislators Figure 4: Cyworld Mini-hompies of Korean legislators Findings As seen in Figure 4, the network structure 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.
65. * Female: Red , Male: Blue , Ruling party: italic From 27th Aug to 10th Sep, 2009 Online presence of Korean politicians Ranking Web visibility No. of Inlinks No. of webpages 1 Geun-Hye Park Geun-Hye Park Young Sun Park 2 Jin Park Dong-Yong Chung Chun Jin Kim 3 Dong-Yong Chung Moon-Soon Choi Jung Bae Cheon 4 Hoi-Chang Lee Gi-Gab Kang Yu Chul Won 5 Sek-Kyun Jung Jung-Sook Kwak Geun-Hye Park 6 Jung-Hoon Kim Gun-Hyun Lee Geun Chan Ryu 7 Young-Jin Kim Woo-Yeo Hwang Dong Chul Kim 8 Sung-Soo Kim Woon-Tae Kang Dong-Yong Chung 9 Hyung-O Kim Jin-ha Hwang Je Se Oh 10 Jun-Pyo Hong Sun-Sook Park Yang Seok Jung
66. Table 1. Summary of comments posted on ten political profile pages between April 2008 and June 2009 . One politician was selected at random from the eighty-one successfully scraped political profiles and the male and female comments posted were taken as the dataset. Politician Male Female Unknown Total 나경원 ( Kyeong-Won Na) 10547 6611 2288 19446 박근혜 ( Geun-Hye Park) 10086 7199 1651 18936 이회창 ( Hoi-Chang Lee) 8970 6284 2380 17634 조경태 ( Kyeong-Tae Cho) 2889 2412 11101 16402 정동영 ( Dong-Yong Chung) 4872 4430 981 10283 문국현 ( Kook-Hyn Moon) 3104 4229 711 8044 강기갑 ( Gi-Gap Kang) 1405 1065 3997 6467 손숙미 ( Sook-Mi Son) 1634 771 586 2991 정몽준 ( Mong-Jun Chung) 1146 409 842 2397 홍정욱 ( Jeong-Wook Hong) 913 753 126 1792
71. Why do they have so many comments? <Comments on Kyeong-Won Na’s mini-hompy> <Comments on Kyeong-Tae Jo’s mini-hompy> Date Total Irrelevant Related in issue on American beef Positive Negative June, 2008 9935 2309 23.24% 378 3.80% 7248 72.95% Date Total Irrelevant Related in Issue on American beef Positive Negative 7th May, 08 7,545 23 0.30% 7,514 99.59% 8 0.11% 8 th May, 08 2,744 6 0.22% 2,734 99.64% 4 0.15% 9 th May, 08 826 2 0.24% 818 99.03% 6 0.73% Total 11,115 31 0.28% 11,066 99.56% 18 0.16%
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74. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITIC WITH E-RESEARCH TOOLS RQ1- The web's 20 most - visible individuals in South Korea
75. RQ1- The web's 20 most - visible individuals in South Korea WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITIC WITH E-RESEARCH TOOLS top online visibility Party Gender Term Constituency 1 박근혜 Park Geun Hye Grand National Party F 4 Daegu 2 진영 Jin Young Grand National Party M 2 Seoul 3 정동영 Jung Dong Young Independent M 3 Jeollabuk-do 4 이회창 Lee Hoi Chang Liberty Forward Party M 3 Chungcheongnam-do 5 정세균 Jung Sek Kyun Democratic Party M 4 Jeollabuk-do 6 김정훈 Kim Jung Hoon Grand National Party M 2 Busan 7 김영진 Kim Young Jin Democratic Party M 5 Gwangju 8 김성수 Kim Sung Soo Grand National Party M 1 Gyeonggi-do 9 김형오 Kim Hyung O Independent M 5 Busan 10 홍준표 Hong Jun Pyo Grand National Party M 4 Seoul 11 이영애 Lee Young Ae Liberty Forward Party F 1 proportional representation 12 이정현 Lee Jung Hyun Grand National Party M 1 proportional representation 13 이정희 Lee Jung Hee Democratic Labor Party F 1 proportional representation 14 박지원 Park Ji Won Democratic Party M 2 Jeollanam-do 15 김태환 Kim Tae Hwan Grand National Party M 2 Gyeongsangbuk-do 16 이상민 Lee Sang Min Liberty Forward Party M 2 Daejeon 17 박선영 Park Sun Young Liberty Forward Party F 1 proportional representation 18 안상수 An Sang Soo Grand National Party M 4 Gyeonggi-do 19 정몽준 Jung Mong Jun Grand National Party M 6 Seoul 20 전여옥 Jeon Yeo Ok Grand National Party F 2 Seoul
79. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITIC WITH E-RESEARCH TOOLS RQ2 – Constituency : Provincial region Online visibilities of the female politicians of the ruling party are higher than those of the opposition parties. Male politicians are just the opposite.
80. WCU WEBOMETRICS INSTITUTE INSTIGATING INTERNET-BASED POLITIC WITH E-RESEARCH TOOLS RQ2- Constituency: Seoul and its vicinities Female politicians of the opposition parties have higher online visibilities than female politicians of the ruling party do. Male politicians are just the opposite.
81. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITIC WITH E-RESEARCH TOOLS RQ2- Constituency : Proportional representation The opposition female politicians ’ online visibilities are higher than female politicians of the ruling party. Male politicians are just the opposite. By comparing the results of the three different types of constituency (i.e. Provincial region, Seoul and its vicinities and Proportional representation) Our data suggest that the politicians of proportional representation are less visible online.
91. - Sentimental Analysis Comments were categorized in one of Following three groups (1) Positive : the post shows respect, support, or rapport with the National Assembly Member. It may suggest policy issues with gentle words or polite words. (2) Negative : the post is hostile, adversarial, or rapport with the National Assembly Member. It may be trying to slander the National Assembly Member, or includes curse words. (3) Irrelevant : The post has nothing to do with the National Assembly Member or his or her policy issues. It is a general comment on politics, or may be SPAM. 4. A case of the Internet politics - A Study on mini-hompy of 18th National Assembly Members
99. *Occurred Words at least 10 times in each politician’s comments positive negative center male female
100. **Occurred Words at least 15 times in each politician’s comments positive negative center male female
101. What types of facial expressions are displayed on official homepages of politicians? More specifically, how do facial images differ among politicians based on their socio-political-demographic attributes? Online Image content analysis of Web 2.0 politics Types Content Smiling face Turning up the corners of the mouth, usually showing their teeth; an upward curving of the corners of the mouth, revealing pleasure, happiness, or amusement; a downward curving of the corners of the eyes, expressing moderate joy. Frowning face Wrinkling of the brow, showing displeasure, anger, unrest, disapproval, and tiredness; a downward curving of the corners of the mouth; staring at something with anger, discontent, or unkindness. No-expression No movement around mouth, eyes, or brow, revealing no emotional information.
102. Politicians’ facial expressions were categorized in one of following three groups: Non face, Smile face, frown face Online Image content analysis of Web 2.0 politics
103. Number and percentage of facial images by type (only on front page) Types Frowning No-expression Smiling Sum Frequency (Percent) 154 (8.20) 471 (25.07) 1,254 (66.74) 1,879 (100.00)
104. ■ The result of image analysis of randomly extracted ten politicians
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112. Affiliation network diagram using pages linked to Lee’s and Park’s sites N = 901 (Lee: 215, Park: 692, Shared: 6)
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114. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS Case 1. 2007 Korean Presidential Election Background Korea boasts the highest proportion of broadband users in the world, and there is a unique evolution of online culture in Korean cyberspace. The country’s impressive level of technological development includes a vibrant online communication environment. The online political climate during the 2007 Korean presidential election can be examined effectively using web-based data analysis. In particular, there were 12 candidates who ran for president and several parties were created in 2007 to support these candidates (see Table 1). The candidates and the parties had to compete against each other to win public attention, particular since it was difficult for citizens to differentiate their stances on issues. Particularly useful for web analysis was the fact that public opinion surveys could not be published within six days before the 2007 election. In 2002, surveys could not be published within 22 days of the presidential election. We will examine how the popularity of individual candidates and parties developed during the 2007 presidential election campaign in South Korea using web-based data collection.
115. WCU WEBOMETRICS INSTITUTE INVESTIGATING INTERNET-BASED POLITICS WITH E-RESEARCH TOOLS Background Case 1. 2007 Korean Presidential Election Table 1. Websites of Presidential Candidates and Parties Candidate Website Candidate’s Party Website Lee Myung-Bak (Lee MB) www.mbplaza.net Grand National Party (GNP) www.hannara.or.kr Chung Dong-Young (Chung DY) www.cdy21.net United New Democratic Party (UNDP) www.undp.kr Lee Hoi-Chang (Lee HC) www.leehc.org Independent Moon Kook-Hyun (Moon KH) www.moon21.kr Creative Party (CKP) www.ckp.kr Kwon Young-Ghil (Kwon YG) www.ghil.net Democratic Labor Party (DLP) www.kdlp.org Rhee In-Je (Rhee IJ) www.ijworld.or.kr Democratic Party (DP) www.minjoo.or.kr Huh Kyung-Young (Huh KY) Same as party site Economy & Republican Party (ERP) www.gonghwa.com Geum Min (Geum M) www.minnmin.net Socialist Party (KSP) www.sp.or.kr Chung Kun-Mo (Chung KM) www.bestjung.kr True Owner Coalition (TOC) www.chamjuin.or.kr Chun Kwan (Chun K) www.chamsaram.or.kr Chamsaram Society Full True Act (CSFTA) Same as candidate site Sim Dae-Pyeng (Sim DY) www.dpsim.co.kr People First Party (PFP) www.mypfp.or.kr Lee Soo-Sung (Lee SS) www.leesoosung.com People’s Coalition (PC) Same as candidate site
121. Network of bilinked citizen blogs URI=Centre DLP=Left GNP=Right Just A-list blogs exchanging links with politicians
122. Bi-linked network of politically active A-list Korean citizen blogs (July 2005) URI=Centre DLP=Left GNP=Right Just A-list blogs exchanging links with politicians
132. Web 1.0, Web 2.0 &Twitter (6/7) Web Types Year Sum of links (Mean) Density Centralisation Gini Coefficient IN OUT Web 1.0 (Homepage) 2000 N=245 373 (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 (Blog) 2005 N=99 652 (6.59) 0.067 22.07 41.66 0.759 2006 589 (5.95) 0.061 20.67 35.10 0.763 Twitter 2009 111 (5.05) 0.240 24.72 39.68 0.408
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134. * A type of tweets - A case Study on twitter of 18th National Assembly Members * Audiences of tweets * Topic of tweets
135. 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
Alexa data: how accurate is it – using audited ABCe figures to check? http://www.malcolmcoles.co.uk/blog/alexa-data-accuracy/ lets you compare stats about websites. But how representative is its data? It's hard to know as it gives figures as %s rather than absolute numbers. So, to find out, I've compared Alexa with the ABCe official audited data for UK newspaper sites - using the figure for the %age of each site's visitors from the UK. As the table shows, Alexa is good but not brilliant. In particular, Alexa consistently underestimates the proportion of users who are from the UK (maybe reflecting its American roots?). However, the Mirror apart, the spread of errors is reasonably consistent.
In journal of interactive marketing pp20-37.
Park & Thelwall, 2008 Park & Thelwall, 2009, JCMC
정당이름 ?
각종 지수들 정리한 것 다 넣기 .
각종 지수들 정리한 것 다 넣기 .
싸이월드 만든 날짜 삽입함
Correlations between indicators?
그림에 대한 설명이 필요함 X, 축과 Y 축에 대한 설명이 필요함
그림의 위 부분은 필요 없다 . 그림 넣으라면 깨끗하게 넣던지 ..
By-elections 결과는 없네
Visitor’s textual comments were gathered and analyzed to determine the conceptual framework of collective identity.
Visitor’s textual comments were gathered and analyzed to determine the conceptual framework of collective identity.
As a matter of fact, the authors attempted to take a random selection of 10 members and examined all facial images displayed within the confines of different homepage menus. Our preliminary results suggest that there are substantial differences in the use of facial images among Assembly members of different party affiliations. For example, there is a distinct difference between the ruling party and the opposition party. We saw the frequent use of non-smiling faces by the opposition members in comparison to the ruling party members. This pilot test is significant, given both the progressive nature of the opposition party and the widespread use of frowning images on its members’ homepages.
I have also visualized distributions of above variables. There are some interesting observations: - Age of politicians are normally distributed. Mean and median is around 56. - The distribution of other variables are skewed, I have not tested yet but it seems as if there is a power law distribution. I might statistically test it later when necessary. - There seems to be a pattern of skewness, see the graph attached.
If there are any significant differences in between gender, party affiliation, constituency, experience, hometown and above variables and in between them.
Lee lost in the vote by delegates, party members and invited non-partisan participants by 432 votes. Their votes accounted for 80 percent of the total score in selecting the nominee. But he won a public opinion poll by 8.5 percentage points over Park. http://gopkorea.blogs.com/south_korean_politics/2007/09/ex-seoul-mayor-.html
Note : Data were dichotomized for the calculation of clustering coefficient and geodesic distance values, and degree centralities were normalized for comparison across networks.
![Investigating Internet-based Korean politics using e-research tools Prof. Han Woo PARK Associate Professor Dept. of Media & Communication, YeungNamUniversity 214-1 Dae-dong, Gyeongsan-si,Gyeongsangbuk-do 712-749, S.Korea [email_address] http://www.hanpark.net Director of WCU Webometrics Institute http://english-webometrics.yu.ac.kr This is in collaboration with Dr. Yon-Soo Lim, Dr. Chieng-Leng Hsu, DPhil. Steven Sams, DPhil, Se-Jung Park, and Ting Wang. Many thanks to my colleagues and assistants!! WCU WEBOMETRICS INSTITUTE](https://image.slidesharecdn.com/overviewofwcuresearch16dec2009sj-091227211508-phpapp01/85/Overview-Of-Wcu-Research-16-Dec2009-Sj-1-320.jpg)
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