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課程名稱 |
社會網絡分析專題
Special Topic on Social Network Analysis |
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開課學期 |
101-2 |
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授課對象 |
文學院 圖書資訊學研究所 |
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授課教師 |
唐牧群 |
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課號 |
LIS5070 |
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課程識別碼 |
126 U1390 |
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班次 |
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學分 |
2 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期二5,6(12:20~14:10) |
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上課地點 |
圖資資訊室 |
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備註 |
本系優先。U選課程，學士班與碩士班同學均可選修。
限碩士班以上 或 限學士班四年級以上
總人數上限：30人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1012SNA |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
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 is a close affinity between SNA and bibliometrics. In LIS, SNA has been used mainly in the study of scholarly communication, as a way of tracing the intellectual influences manifested in 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 within an organization. With the recent popularity of social networking sites, a growing availability of network data makes it possible to study item-item simiarity and relatedness within a network of people, documents, and websites.
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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", "80/20 rule", 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, and recommendation networks.
3. give students hand-on experiences with collecting and analyzing network data centered on the software packages UCINET and NetDraw.
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課程要求 |
Grades and Assignments
1. Exercises (30%)
Students will be given three class exercises throughout the semester, each will account of 10% of your final grade.
2. Article review (30%)
Each student is required to report two empirical studies that have adopted SNA methods. One of the articles will be selected from the “article review” section on the syllabus (see below); the other will be chosen from the results of your own literature review. Ideally, the article you choose should serve as an “exemplar” for the type of research you would like to propose in your final project. Choose the article that interests you, either methodologically or theoretically, so you can build your own research proposal on it. Discuss with me before you make your choice.
No written report for this assignment. Prepare a 20 minutes power point presentation and a 10 minutes Q&A session. The power point file is to be posted on the class website one day before the date on which your presentation is scheduled.
3. Research proposal (30%)
This will be an independent project from graduate students; and a group project for undergraduates.
Each group (for graduate students, each individual) will write a research proposal that informed by theories or methods introduced in the class, which is due at the end of the semester.
As the focus of the paper will be the methodology, a lengthy literature review is not required. It will be a user study that consists of the following components:
a. Theoretical framework and problem statement (1-2 pages)
b. Study objectives (1-2 pages)
c. Research Questions (1-2 pages)
d. Research procedures (methodology, design, instruments) (4-8 pages)
e. Expected difficulties (1-2) pages
f . Presentation of the project to the class
4. Participation (10%)
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
Required readings
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.
Hanneman, R. A. & Riddle, M. (2005). Introduction to social network methods. CA: University of California. (at http://faculty.ucr.edu/~hanneman/)
Haythornthwaite, C. & Wellman, B. (1998). Work, friendship, and media use for information exchange in a networked organization. Journal of the American Society for Information Science, 49(12), 1101-1114.
Review Articles
Bernard, H.R., Killworth, P.D., McCarty, C., Shelley, G.A., & Robinson, S. (1990). Comparing four Different Methods for Measuring Personal Social Networks. Social Networks, 12, 179-216.
Borgatti, S. P., & Everett, M. G. (1992). Notions of Position in Social Network Analysis. Sociological Methodology, 22, 1-35.
Bonhard, P. & Sasse, M (2006). ’Knowing me, knowing you’ – Using profiles and social networking to improve recommendsystems. BT Technology Journal, 24(3), 84-98.
Saverio Perugini, Marcos Andr Gonalves, and Edward A. Fox. Recommender systems research: A
connection-centric survey. Journal of Intelligent Information Systems, 23(2):107 — 143, September 2004.
Ellison, N. B., Steinfeld, C., & Lampe, C. (2007). The benefits of Facebook ‘‘Friends:’’ Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), article 1.
Marsden, P. V. (1990). Network Data and Measurement. Annual Review of Sociology, 16, 435-463.
Mislove, A., M. Marcon, K. Gummadi, P. Druschel, and B. Bhattacharjee. Measurement and analysis of online social networks. In IMC, 2007.
Moody, J. & White, D. R. (2003). Structural Cohesion and Embeddedness: A Hierarchical Concept of Social Groups. American Sociological Review, 68(1), 103-127.
Newman, M. E. J. (2004). Coauthorship Networks and Patterns of Scientific Collaboration. Proceedings of the National Academy of Sciences of the United States of America, 101(1), 5200-5205.
Sandstrom, P.E. (2001). Scholarly communication as a socioecological system. Scientometrics, 51(3), 573-605
Watts, D. J. (2004). The “New” Science of Networks. Annual Review of Sociology, 30, 243-270.
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評量方式
(僅供參考) |
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