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Group 1: 5 th presentation

Group 1: 5 th presentation. Comparing academic hyperlink structure with co-authorship pattern in Korea Hyo Kim @ Ajou University Han Woo Park @ YeungNam University. Hyo Kim. College of Information Technology Media division Ajou University Korea (South) Tel) +82-31-219-1858

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Group 1: 5 th presentation

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  1. Group 1: 5th presentation Comparing academic hyperlink structure with co-authorship pattern in Korea Hyo Kim @ Ajou University Han Woo Park @ YeungNam University

  2. Hyo Kim College of Information Technology Media division Ajou University Korea (South) Tel) +82-31-219-1858 E-mail) hkimscil@commres.org

  3. Han Woo Park School of Social Sciences Yeung Nam University Korea (South) hanpark@yumail.ac.kr http://www.hanpark.net

  4. Study • Structural characteristics of academic hyperlinks among universities in Korea • Relationship between hyperlinks and productiveness • Speculation of actual communication patterns from the hyperlink activities • Via SNA (social network analysis) approach

  5. Data I • http://www.braintrack.com/ • The most visible two universities in each local region in Korea (South part, N = 30) • http://altavista.com/ • Number of in-links and out-links to the universities in the data set • ISI database • the number of research articles listed in the SCI index published in each university • 2 univ. dropped (N = 28)

  6. Data II – # of hyperlinks

  7. Data III

  8. Dichotomization for CONCOR • From the initial matrix (Data II) • Replacing binary values • Average of the matrix = 17.11 • Cells bellow the mean = 0 • Cells greater than or equal to (GE) the mean = 1 • New data matrix (see next page)

  9. CONCOR - dichotomized

  10. Groups identified by CONCOR

  11. MDS graph Groups Identified (from CONCOR)

  12. Relationships among the groups

  13. 1 A B .31 .79 .91 D .93 C .53 Visualization of group rel. • Group A, B, C, D (identified from CONCOR) can be visualized

  14. Group rel. • Members in group A = the strongest rel (regarding hyperlinks, value = 1) • Members in group C = strong rel (value = .53) • Strong rel between group A and C (A->C = .93; C -> A = .79) • Members in group B = isolated • Members in group D = no strong hyperlink activity among themselves, but, strong hyperlink-receivers (value = .91) and weak hyperlink maker (value = .31)

  15. ANOVA • Are these groups meaningful in terms of the number of links (in and out); and the number of articles? • In-links: F (3, 24) = 9.73, p < .0001 • Out-links: F (3, 24) = 62.79, p < .0001 • Articles: F (3, 24) = 8.26, p < .0001 • Group A differs from all other universities in terms of the number of published journal articles, which means the members of group A are strong research universities.

  16. QAP (dyadic rel) • CONCOR test just reveals general relationships among members in each group or among groups. • ANOVA test does not reveal relationships. • QAP will reveal specific relationship between universities and SCI articles at a dyadic level.

  17. QAP test • IV: in- and out-links matrices • DV: matrix of the number of articles

  18. DV = SCI journal articles • The number of SCI journal articles • The data set is not usable for QAP test because it is an attribute data (just one raw, it has). • So, the data is transformed into matrix (via obtaining the dyadic difference of the number of articles between two universities)

  19. DV = SCI journal articles • Each number in a cell means the absolute difference (of the number of articles) between two universities

  20. QAP result • R-square = 35.6% • Both In and Out matrix are significantly related to the DV matrix (# of articles; In = .41; Out = .24), which means . . . • at a dyadic level, if one university has more links (both in and out), the university produces more SCI journal articles. • Caution: a kind of regression test, which means • no causal relationship between IVs and DV are assumed. • Therefore, we can just speculated that SCI journals are significantly related to number of links.

  21. Study discussion • With SNA, we explored • At structural level • The structural characteristic of the whole matrix of in and out hyperlinks. • Four groups identified from the structural characteristics • Four groups differed from # of SCI articles, which means hyperlinking activity is related to the journal publication.

  22. Study Discussion II • At a dyadic level, • Specifically, # of SCI articles is related to # of in and out links between two universities.

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