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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 |
103-1 |
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授課對象 |
文學院 圖書資訊學系 |
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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 |
126EU1390 |
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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 |
本課程以英語授課。U選課程，大學部與研究所學生均可修習。
總人數上限：30人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1031LIS_SNA |
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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 |
I. Participation (10%)
II. Group projects
Students will work in pairs to conduct three group projects (except for the final project, which the graduates students will work indepentently):
1. Class assignments (30%)
All Students will be given two class exercises in the semester. These assignments are designed to give you hand-on experiences with collecting, inputting and analyzing network data. You will be asked to work with two datasets upon which you are to perform various SNA methods and from which you will also generate and test your own hypotheses.
2. Empirical study review (20%)
Each group is required to choose and give a 20 minutes power point presentation of a SNA related empirical study. You can find the list of "review articles " in the reference list. The date for each of the reviewed articles has been specified in the "Course Schedule" so in choosing the article you want to review you are also determining when you will do the presentation.
No written report for this assignment. Prepare a 20 minutes power point presentation and a 5-10 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 (40%) *Graduate students will work individually for this assignment.
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 page)
c. Research Questions (1 page)
d. Research procedures (methodology, design, instruments) (1-3 pages)
E. Initial results and discussion
F. Powerpoint presentation of your project |
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預期每週課後學習時數 |
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Office Hours |
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參考書目 |
Required readings
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.
Hanneman, R. A. & Riddle, M. (2005). Introduction to social network methods. CA:
University of California. (at http://faculty.ucr.edu/~hanneman/)
McCain, K. W. (1990). Mapping authors in intellectual space: A technical
overview. Journal of the American Society for Information Science, 41, 433–443.
Newman, M.E.J. & Girvan, M. (2004). Finding and evaluating community structure
in network. Physical Review. 69.
Perugini, Saverio 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. |
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指定閱讀 |
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評量方式
(僅供參考) |
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