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�ݺ�ߣshows by User: soyoungyu / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: soyoungyu / Tue, 10 Mar 2015 01:39:49 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: soyoungyu Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro level /soyoungyu/detecting-collaboration-patterns-among-ischools-by-linking-scholarly-communication-to-social-networking-at-the-macro-and-micro-level 20130814detectingcollaborationpatternsamongischoolsbylinkingscholarly-150310013949-conversion-gate01
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 compared statistically 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.]]>
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 compared statistically 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.]]> Tue, 10 Mar 2015 01:39:49 GMT /soyoungyu/detecting-collaboration-patterns-among-ischools-by-linking-scholarly-communication-to-social-networking-at-the-macro-and-micro-level soyoungyu@slideshare.net(soyoungyu) Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro level soyoungyu 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 compared statistically 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20130814detectingcollaborationpatternsamongischoolsbylinkingscholarly-150310013949-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> 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 compared statistically 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.

Detecting collaboration patterns among iSchools by linking scholarly communication to social networking at the macro and micro level from SoYoung YU

]]> 504 3 https://cdn.slidesharecdn.com/ss_thumbnails/20130814detectingcollaborationpatternsamongischoolsbylinkingscholarly-150310013949-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Tracking Trends in Korean Information Science Research, 2000-2011 /slideshow/tracking-trends-in-korean-information-science-research-20002011/14915608 seoyucollnet201220121024-121027190741-phpapp01
This is a presentation file of "Tracking Trends in Korean Information Science Research, 2000-2011" which was published in COLLNET 2012 proceeding, October 23rd, 2012. If you need a full paper of it, feel free to contact So Young Yu (soyoung.yu21@gmail.com)]]>
This is a presentation file of "Tracking Trends in Korean Information Science Research, 2000-2011" which was published in COLLNET 2012 proceeding, October 23rd, 2012. If you need a full paper of it, feel free to contact So Young Yu (soyoung.yu21@gmail.com)]]> Sat, 27 Oct 2012 19:07:39 GMT /slideshow/tracking-trends-in-korean-information-science-research-20002011/14915608 soyoungyu@slideshare.net(soyoungyu) Tracking Trends in Korean Information Science Research, 2000-2011 soyoungyu This is a presentation file of "Tracking Trends in Korean Information Science Research, 2000-2011" which was published in COLLNET 2012 proceeding, October 23rd, 2012. If you need a full paper of it, feel free to contact So Young Yu (soyoung.yu21@gmail.com) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/seoyucollnet201220121024-121027190741-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> This is a presentation file of "Tracking Trends in Korean Information Science Research, 2000-2011" which was published in COLLNET 2012 proceeding, October 23rd, 2012. If you need a full paper of it, feel free to contact So Young Yu (soyoung.yu21@gmail.com)

Tracking Trends in Korean Information Science Research, 2000-2011 from SoYoung YU

]]> 431 4 https://cdn.slidesharecdn.com/ss_thumbnails/seoyucollnet201220121024-121027190741-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

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0 https://cdn.slidesharecdn.com/profile-photo-soyoungyu-48x48.jpg?cb=1589109048 Data Science is supposed to be defined by its diversity and potentials of applying multi-disciplinary approach, not by the size of it or current techniques to apply. Data are ready to tell their stories in their own terms, and I'm READY to interpret what they tell to targeted audience of technical, non-technical, or business background for their decision-making and problem-solving. The boughs that bear most hang lowest. lifeinthemetrics.wordpress.com/ https://cdn.slidesharecdn.com/ss_thumbnails/20130814detectingcollaborationpatternsamongischoolsbylinkingscholarly-150310013949-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds soyoungyu/detecting-collaboration-patterns-among-ischools-by-linking-scholarly-communication-to-social-networking-at-the-macro-and-micro-level Detecting collaboratio... https://cdn.slidesharecdn.com/ss_thumbnails/seoyucollnet201220121024-121027190741-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/tracking-trends-in-korean-information-science-research-20002011/14915608 Tracking Trends in Kor...