Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels
Information schools (iSchools) have grown along with heightened understanding of the rapid changes taking place in the information society and in the humanities. This growth has led to the characteristics of multidisciplinarity and the need for ongoing discussion and collaboration in information fie...
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sg-ntu-dr.10356-1542292021-12-22T20:10:38Z Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels Yu, So-Young Library and information science Information schools (iSchools) have grown along with heightened understanding of the rapid changes taking place in the information society and in the humanities. This growth has led to the characteristics of multidisciplinarity and the need for ongoing discussion and collaboration in information field (i-Field) research in terms of human behaviors and information technology. To promote collaboration in the context of research and education, it is necessary to understand the current activities of iSchools in relation to their collaboration patterns. This study analyzed the research patterns among iSchools at the macro and micro levels, and combined the analysis results. For the analysis, 41 iSchools were identified from the iSchool directory. Co-authorship and an institution-profiling network were extracted from conference papers and posters presented at the iConference 2008-2013 to mine scholarly communication patterns. Social networks (“friendship” networks) among them were also extracted from Twitter by collecting their common followees to identify their interest in current public issues. The network analysis was performed at the micro and macro levels. In the micro-level analysis, the structures of social networking and scholarly communication among 41 iSchools were constructed and compared statistically by executing quadratic assignment procedure (QAP) correlation. The QAP correlation analysis determines whether a relationship exists between two particular nodes in two networks at the same time. At the macro level, comparison between the top interest in social networking and that of scholarly communication was performed by revealing top co-word networks. Additionally, co-authorship patterns and institution profiling patterns among 196 institutions, including the 41 iSchools identified in scholarly communication, were comparedstatistically to identify similarities and differences in communication patterns of iSchools compared to non-iSchools. The analysis provided evidence of the current prominent collaborating bodies and their neighbors as proactive actors accelerating scholarly communication and social networking. The social networking pattern and institution-profiling pattern were significantly related at the micro level, and the co-authorship pattern was significantly related to the institution-profiling pattern at macro-level. Additionally, iSchools that actively elaborate social networking and scholarly communication at the micro or macro levels were identified and compared to determine whether iSchools that could bridge other iSchools and non-iSchools in both social networking and research. The significant interest in social networking revealed in this study was related to IT trends and higher education while the research interest in the iField was related to linking information science to society, technology, and culture. Published version 2021-12-16T04:07:05Z 2021-12-16T04:07:05Z 2013 Journal Article Yu, S. (2013). Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels. Library and Information Science Research E-Journal, 23(2), 1-13. https://dx.doi.org/10.32655/LIBRES.2013.2.4 1058-6768 https://hdl.handle.net/10356/154229 10.32655/LIBRES.2013.2.4 2 23 1 13 en Library and Information Science Research E-Journal © 2013 So-Young Yu. All rights reserved. application/pdf |
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Library and information science Yu, So-Young Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels |
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Information schools (iSchools) have grown along with heightened understanding of the rapid changes taking place in the information society and in the humanities. This growth has led to the characteristics of multidisciplinarity and the need for ongoing discussion and collaboration in information field (i-Field) research in terms of human behaviors and information technology. To promote collaboration in the context of research and education, it is necessary to understand the current activities of iSchools in relation to their collaboration patterns. This study analyzed the research patterns among iSchools at the macro and micro levels, and combined the analysis results. For the analysis, 41 iSchools were identified from the iSchool directory. Co-authorship and an institution-profiling network were extracted from conference papers and posters presented at the iConference 2008-2013 to mine scholarly communication patterns. Social networks (“friendship” networks) among them were also extracted from Twitter by collecting their common followees to identify their interest in current public issues. The network analysis was performed at the micro and macro levels. In the micro-level analysis, the structures of social networking and scholarly communication among 41 iSchools were constructed and compared statistically by executing quadratic assignment procedure (QAP) correlation. The QAP correlation analysis determines whether a relationship exists between two particular nodes in two networks at the same time. At the macro level, comparison between the top interest in social networking and that of scholarly communication was performed by revealing top co-word networks. Additionally, co-authorship patterns and institution profiling patterns among 196 institutions, including the 41 iSchools identified in scholarly communication, were comparedstatistically to identify similarities and differences in communication patterns of iSchools compared to non-iSchools. The analysis provided evidence of the current prominent collaborating bodies and their neighbors as proactive actors accelerating scholarly communication and social networking. The social networking pattern and institution-profiling pattern were significantly related at the micro level, and the co-authorship pattern was significantly related to the institution-profiling pattern at macro-level. Additionally, iSchools that actively elaborate social networking and scholarly communication at the micro or macro levels were identified and compared to determine whether iSchools that could bridge other iSchools and non-iSchools in both social networking and research. The significant interest in social networking revealed in this study was related to IT trends and higher education while the research interest in the iField was related to linking information science to society, technology, and culture. |
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Article |
author |
Yu, So-Young |
author_facet |
Yu, So-Young |
author_sort |
Yu, So-Young |
title |
Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels |
title_short |
Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels |
title_full |
Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels |
title_fullStr |
Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels |
title_full_unstemmed |
Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro levels |
title_sort |
detecting collaboration patterns among ischools by linking scholarly communication to social networking at the macro and micro levels |
publishDate |
2021 |
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https://hdl.handle.net/10356/154229 |
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1720447081388179456 |