課程資訊
課程名稱
社會網絡分析專題
Special Topic on Social Network Analysis 
開課學期
109-2 
授課對象
文學院  圖書資訊學系  
授課教師
唐牧群 
課號
LIS5070 
課程識別碼
126 U1390 
班次
 
學分
2.0 
全/半年
半年 
必/選修
選修 
上課時間
星期三6,7(13:20~15:10) 
上課地點
圖資資訊室 
備註
U選課程,學士班與碩士班學生均可選修
總人數上限:30人 
 
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課程概述

This is an instrouctory course to the basic concepts in social network analysis, with an emphasis on its application in bibliometrics and knowledge management. Recent years have witnessed an explosion of interest in social network analysis (SNA). SNA techniques have been applied in a wide range of domains. There has been a close affinity between SNA and bibliometrics in LIS where SNA has been used applied in the study of scholalry collaboration and citation analysis, as a way of tracing the intellectual influences manifested in collaboratiion and citation behaviors among scholars. In knowledge management, SNA has also been used to assess the structure component of social capital, which explains the patterns of information exchange and team performance within an organization. With the recent popularity of social networking sites, a growing availability of network data also makes it possible to study similarity and relatedness within a network of people, documents, and websites. 

課程目標
This class is designed for advanced undergraduates or graduate students who wish to acquire a basic understanding of SNA and explore the possibility of utilizing SNA for their research. The class seeks to:
1. provide a survey of the network perspective on a wide range of theories and phenomena such as "the small world", "strong/weak ties", and power law, with a specific focus on their implications on social and behavioral sciences.
2. introduce students to empirical studies utilizing SNA methods in areas such as scholarly communication/bibliometrics, social capital, education, and recommendation networks.
3. give students hand-on experiences with collecting and analyzing network data centered on the software packages UCINET, NetDraw, VosViewer, and Gephi. 
課程要求
Assignments and Grading

I. Participation (10%)
II. Group projects
Students will form into groups of two to three to complete the following group project:

1. Class assignments (60%)
All group will complete and turn in four class assignment over the course of the semester. These assignments are designed to give you hand-on experiences with collecting, inputting and analyzing network data.

2. Final project (30%)
Each group will propose and turn in an empirical research using social network analysis for the final project. The analysis will be driven by research questions or hypotheses (1 to 3) developed within each group. You are to perform various visualization and network analytical techniques we have covered in the classes, including cohesion, centrality, community-detection, and hypothesis-testing. The final project includes also a PowerPoint presentation of your results. Your final project will contain the following components:
a. Theoretical framework and research questions (1-2 pages)
b. Research procedures (data collection procedures, measures and analytical techniques) (1-5 pages)
c. Initial results and discussion d. PowerPoint presentation of your project 
Office Hours
另約時間 
參考書目
SNA resources and data online
A very user friendly instroduction to network theory
Demo Gephi Citation Network Analysis with Scopus Data
UCI network data repository
Stanford large network data collection
Datasets for Gephi
Marvel universe datasets for Gephi

References
Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing social networks. SAGE Publications Limited.
Borgatti, S. P., A. Mehr, D. J. Brass, G. Labiance, (2009). Network Analysis in the Social Sciences. Science (323), p. 892-895.
Burt, R.S. (2005). Brokerage and Closure: an introduction to social capital. Oxford.
Burt, R. S. (2000). The Network Structure of Social Capital. Research in Organizational Behavior, 22, 345-423.
Barabasi, A. L. (2003) . Linked: How Everything Is Connected to Everything Else and What It Means. New York: Plume.
Christakis, N. A. (2010). Connected: Amazing Power Of Social Networks and How They Shape Our Lives. UK: HarperCollins.
Easley, D. & Kleinberg, J. (2010). Networks, Crowds, and Markets: Reasoning About a Highly Connected World. UK:Cambridge University Press.
Fisher, D., Smith, M., & Welser, H. T. (2006, January). You are who you talk to: Detecting roles in usenet newsgroups. In System Sciences, 2006. HICSS'06. Proceedings of the 39th Annual Hawaii International Conference on (Vol. 3, pp. 59b-59b). IEEE
Golbeck, J. (2013). Analyzing the social web. Newnes.
Hanneman, R. A. & Riddle, M. (2005). Introduction to social network methods. CA: University of California. (at http://faculty.ucr.edu/~hanneman/)
Glanzel, W., & Schubert, A. (2005). Analysing scientific networks through co-authorship. In Handbook of quantitative science and technology research (pp. 257-276). Springer Netherlands.
McCain, K. W. (1990). Mapping authors in intellectual space: A technical overview. Journal of the American Society for Information Science, 41, 433–443.
Milgram, Stanley. "The small world problem." Psychology today 2.1 (1967): 60-67.
Reagans, R., & Zuckerman, E. W. (2001). Networks, diversity, and productivity: The social capital of corporate R&D teams. Organization science, 12(4), 502-517.
Sandstrom, P.E. (2001). Scholarly communication as a socioecological system. Scientometrics, 51(3), 573-605.
Borgatti, S. P., & Everett, M. G. (1992). Notions of Position in Social Network Analysis. Sociological Methodology, 22, 1-35.
Gilbert, E. & Karahalios, K. (2009). Predicting tie strength with social media. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 211-220).
Klavans, R., & Boyack, K. W. (2006). Identifying a better measure of relatedness for mapping science. Journal of the American Society for Information Science and Technology, 57(2), 251-263.
Kadushin, C. (2012). Understanding social networks: Theories, concepts, and findings. Oxford University Press.
Marsden, P. V. (1990). Network Data and Measurement. Annual Review of Sociology, 16, 435-463.
Moody, J. (2004). The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American sociological review, 69(2), 213-238.
Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience. Scientometrics, 82(2), 263-287.
Scott, J., & Carrington, P. J. (Eds.). (2011). The SAGE handbook of social network analysis. SAGE publications.
Mislove, A., M. Marcon, K. Gummadi, P. Druschel, and B. Bhattacharjee. Measurement and analysis of online social networks. In IMC, 2007.
Watts, D. J. (2004). The “New” Science of Networks. Annual Review of Sociology, 30, 243-270. 
指定閱讀
 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
第1週
2/24  Introduction; the network perspective in social sciences and bibliometrics 
第2週
3/3  Intro to network data UCINET and NetDraw, Gephi, datasets Readings Golbeck, J. (2013). Analyzing the social web. Ch. 2. Nodes, Edges, and network measures 
第3週
3/10  Data collection; Two-modes networks Readings Borgatti, S. P., A. Mehr, D. J. Brass, G. Labiance, (2009). Network anaysis in social science 
第4週
3/17  Graphs Readings Golbeck, J. (2013). Analyzing the social web. Ch. 3 
第5週
3/24  Cohesion, E-I (homophily test) Readings Hanneman & Riddle,( 2005 ) Ch. 7.8 
第6週
3/31  Network centrality and centralization; central-periphery structure/coreness First assignment due (Cohesion, E-I) Readings Hanneman & Riddle,( 2005 ) Ch. 10 
第7週
4/7  Netowrk dynamics Readings Aiello, L. M. et al. (2010). Link creation and profile alignment in the aNobii social network 
第8週
4/14  Small world, clustering coefficient; Strong ties and weak ties; traid closure Readings Milgram, Stanley. "The small world problem." Psychology today 2.1 (1967): 60-67. 
第9週
4/21  Preferential attachment Readings Barabasi (2003) Ch 5, 6, 7 
第10週
4/28  Community-detection (clustering) Girvan Newman Modularity. Louvain method Second assignment due (Centrality) Readings Borgatti, Everett, & Johnson (2018). Analyzing social networks: Ch. 11 Subgroup, 
第11週
5/5  Similarity and structural equivalence Readings Hanneman & Riddle,( 2005 ) Ch. 13 
第12週
5/12  Social network and Social capital Readings Borgatti, S., Jones, B. C., and Everett, M.G.(1998). Network Measures of Social Capital. Connection 21(2). 
第13週
5/19  Hypothesis testing with networked data; Multi-plex networks 
第14週
5/26  Vosviewer demo; Bibliometrics and network analysis: co-authorship network Third assignment due (Community-detection, hypothesis testing) 
第15週
6/2  Network filtering procedures Readings Borgatti, Everett, & Johnson (2018). Analyzing social networks: Ch. 14 Large network 
第16週
6/9  Discussion of your final project 
第17週
6/16  Discussion of your final project 
第18週
6/23  Final presentation Final project due