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Representing Social Network and Research Diversity of Library and Information Science in Taiwan Using Thesis Advisory Network
thesis committee,social network,research diversity,Library and Information Science,
|Publication Year :||2013|
Citation analysis has long been adopted to visually present a knowledge domain. Drawing from thesis committee membership data, the study took a social analytical approach to analyze the social and intellectual structure of the field of LIS (Library and Information Science in Taiwan). Specifically, the study attempt to study: firstly, the faculty collaboration network; and secondly, the degree and nature of inter- disciplinary collaboration, as reflected in the composition of the thesis committees. A total 751 Master’s theses published by the eight LIS in the periods from 2006 to 2011 were analyzed. Data extracted included the composition of each committee member- ship and research topics covered in these theses. Furthermore, data about the faculty’s background were also collected, including gender, seniority, department affiliation, highest degree received, with which the faculty’s degree of interdisciplinary collaboration, as reflected in the thesis committee they appeared, could be analyzed.
With the theses committee composition data, networks of faculty collaboration were generated where each faulty member were represented by a node, and the strength of their collaboration was represented by the frequency of their co-appeared in these committees. Various network measures, such as centrality, clustering coefficient, E-I index were used to study the cohesion of each department and the LIS filed as a whole. Three diversity measures: Shannon, Simpson, and Gini coefficient, were used to assess the degree of interdisciplinarity of each department and faculty. Regression analyses showed that the number of these advised, seniority, and thesis topic diversity were the significant predictor of a faculty’s centrality in the LIS network.
|Appears in Collections:||圖書資訊學系|
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