Kor univ aoir2004

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Kor univ aoir2004

  1. 1. Group 1: 5 th presentation <ul><li>Comparing academic hyperlink structure with co-authorship pattern in Korea </li></ul><ul><li>Hyo Kim </li></ul><ul><li>@ Ajou University </li></ul><ul><li>Han Woo Park </li></ul><ul><li>@ YeungNam University </li></ul>
  2. 2. Hyo Kim <ul><li>College of Information Technology </li></ul><ul><li>Media division </li></ul><ul><li>Ajou University </li></ul><ul><li>Korea (South) </li></ul><ul><li>Tel) +82-31-219-1858 </li></ul><ul><li>E-mail) hkimscil@commres.org </li></ul>
  3. 3. Han Woo Park <ul><li>School of Social Sciences </li></ul><ul><li>Yeung Nam University </li></ul><ul><li>Korea (South) </li></ul><ul><li>[email_address] </li></ul><ul><li>http://www.hanpark.net </li></ul>
  4. 4. Study <ul><li>Structural characteristics of academic hyperlinks among universities in Korea </li></ul><ul><li>Relationship between hyperlinks and productiveness </li></ul><ul><li>Speculation of actual communication patterns from the hyperlink activities </li></ul><ul><li>Via SNA (social network analysis) approach </li></ul>
  5. 5. Data I <ul><li>http://www.braintrack.com/ </li></ul><ul><ul><li>The most visible two universities in each local region in Korea (South part, N = 30) </li></ul></ul><ul><li>http://altavista.com/ </li></ul><ul><ul><li>Number of in-links and out-links to the universities in the data set </li></ul></ul><ul><li>ISI database </li></ul><ul><ul><li>the number of research articles listed in the SCI index published in each university </li></ul></ul><ul><ul><li>2 univ. dropped (N = 28) </li></ul></ul>
  6. 6. Data II – # of hyperlinks … … … … … … … … 2 2 2 5 10 hannam … 0 0 1 3 4 keimyung … 1 11 13 36 kyungpook … 9 9 8 20 donga … 25 14 26 95 pusan … 16 10 14 90 korea … 67 31 86 139 snu - - - - - - Universities
  7. 7. Data III … … … 182 104 chosun 287 1088 chonnam 69 56 inchon 137 27 keimyung 371 152 kyungpook 171 158 donga 373 393 pusan 471 324 korea 1070 1224 snu outdegree Indegree
  8. 8. Dichotomization for CONCOR <ul><li>From the initial matrix (Data II) </li></ul><ul><li>Replacing binary values </li></ul><ul><ul><li>Average of the matrix = 17.11 </li></ul></ul><ul><ul><li>Cells bellow the mean = 0 </li></ul></ul><ul><ul><li>Cells greater than or equal to (GE) the mean = 1 </li></ul></ul><ul><li>New data matrix (see next page) </li></ul>
  9. 9. CONCOR - dichotomized … … … … … … … … 0 0 0 0 1 Kyung pook … 0 0 0 0 1 donga … 1 0 0 1 1 pusan … 0 0 0 0 1 korea … 1 1 1 1 0 snu … Kyung pook donga pusan korea snu  
  10. 10. Groups identified by CONCOR
  11. 11. MDS graph <ul><li>Groups </li></ul><ul><li>Identified </li></ul><ul><li>(from </li></ul><ul><li>CONCOR) </li></ul>
  12. 12. Relationships among the groups 0.31       Average 0.06 0 0 0.31 D 0.089 0.53 0 0.79 C 0 0 0.33 0 B 0.91 0.93 0 1 A D C B A  
  13. 13. Visualization of group rel. <ul><li>Group A, B, C, D (identified from CONCOR) can be visualized </li></ul>.31 .53 .79 .91 1 .93 A B C D
  14. 14. Group rel. <ul><li>Members in group A = the strongest rel (regarding hyperlinks, value = 1) </li></ul><ul><li>Members in group C = strong rel (value = .53) </li></ul><ul><li>Strong rel between group A and C (A->C = .93; C -> A = .79) </li></ul><ul><li>Members in group B = isolated </li></ul><ul><li>Members in group D = no strong hyperlink activity among themselves, but, strong hyperlink-receivers (value = .91) and weak hyperlink maker (value = .31) </li></ul>
  15. 15. ANOVA <ul><li>Are these groups meaningful in terms of the number of links (in and out); and the number of articles? </li></ul><ul><ul><li>In-links: F (3, 24) = 9.73, p < .0001 </li></ul></ul><ul><ul><li>Out-links: F (3, 24) = 62.79, p < .0001 </li></ul></ul><ul><ul><li>Articles: F (3, 24) = 8.26, p < .0001 </li></ul></ul><ul><ul><ul><li>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. </li></ul></ul></ul>
  16. 16. QAP (dyadic rel) <ul><li>CONCOR test just reveals general relationships among members in each group or among groups. </li></ul><ul><li>ANOVA test does not reveal relationships. </li></ul><ul><li>QAP will reveal specific relationship between universities and SCI articles at a dyadic level. </li></ul>
  17. 17. QAP test <ul><li>IV: in- and out-links matrices </li></ul><ul><li>DV: matrix of the number of articles </li></ul>
  18. 18. DV = SCI journal articles <ul><li>The number of SCI journal articles </li></ul><ul><li>The data set is not usable for QAP test because it is an attribute data (just one raw, it has). </li></ul><ul><li>So, the data is transformed into matrix (via obtaining the dyadic difference of the number of articles between two universities) </li></ul>717 inha 635 cnu 62 hannam 159 keimyung 951 kyungpook 191 donga 757 pusan 1193 korea 3828 snu sci
  19. 19. DV = SCI journal articles <ul><li>Each number in a cell means the absolute difference (of the number of articles) between two universities </li></ul>… … … … … … … 0 566 1002 3637 donga … 566 0 436 3071 pusan … 1002 436 0 2635 korea … 3637 3071 2635 0 snu … donga pusan korea snu  
  20. 20. QAP result <ul><li>R-square = 35.6% </li></ul><ul><li>Both In and Out matrix are significantly related to the DV matrix (# of articles; In = .41; Out = .24), which means . . . </li></ul><ul><li>at a dyadic level, if one university has more links (both in and out), the university produces more SCI journal articles. </li></ul><ul><li>Caution: a kind of regression test, which means </li></ul><ul><li>no causal relationship between IVs and DV are assumed. </li></ul><ul><li>Therefore, we can just speculated that SCI journals are significantly related to number of links. </li></ul>0.96 0.04 0.04 0.41 IN 0.993 0.007 0.007 0.24 OUT 0.042 0.958 0.958 0 Intercept p high p low P beta  
  21. 21. Study discussion <ul><li>With SNA, we explored </li></ul><ul><li>At structural level </li></ul><ul><ul><li>The structural characteristic of the whole matrix of in and out hyperlinks. </li></ul></ul><ul><ul><li>Four groups identified from the structural characteristics </li></ul></ul><ul><ul><li>Four groups differed from # of SCI articles, which means hyperlinking activity is related to the journal publication. </li></ul></ul>
  22. 22. Study Discussion II <ul><li>At a dyadic level, </li></ul><ul><ul><li>Specifically, # of SCI articles is related to # of in and out links between two universities. </li></ul></ul>

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