社會網絡研究
Research on Social Network Analysis
| 節 | 週二 |
|---|---|
2 09:00–09:50 | 社會網絡研究 HK206 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
By the end of the semester: 1. Students should be able to exhibit correct and comprehensive knowledge about social network theories and fundamental concepts of social network analysis; 2. Students should display a good understanding about the extant techniques of social network analysis; 3. Students should be able to exhibit the ability to conduct a research project independently, including: observing a social phenomenon and coming up with a research problem, employing appropriate network-related theoretical frameworks, developing hypotheses/research questions, designing and executing a network study, analyzing network data, and presenting the results following academic standards; 4. Students will develop the research habit of employing a (an alternative) network view of observing and analyzing human behaviors.
This course is designed to introduce students to the area of social network analysis (SNA), including the theories and the techniques of conducting social network analysis. In particular, students will learn the theories and concepts (e.g., homophily, triadic closure, network evolution, dyadic and dependency nature of network data) key to the development of social network analysis. Parallel to the theory exposure, students will be equipped with the skills of conducting basic and advanced social network analyses through hands-on exercises. The course will culminate in the production of a research paper, which requires students to apply social network theory and analytical approaches to examine a research problem. This paper should match the expectations for a conference paper in the communication field.
The course will be conducted in the form of a seminar, supplemented by in-class exercises and lab tutorials. Four lab sessions will be conducted to help students learn how to use dedicated software (e.g., UCINET, NodeXL) to perform basic and advanced network analyses.
Percent of grade Class participation 20% SNA exercises Exercise 1 10% Exercise 2 10% Exercise 3 5% Research project Proposal and presentation 10% Literature review 15% Method and findings 15% Final paper and presentation 15% ----------------------------------------------------- 100%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course Overview Introduction to Social Network Analysis |
| 第 2 週 | Theories and Key Concepts of Social Network Analysis |
| 第 3 週 | Network Theorizing on Self-Interest and Collective Action |
| 第 4 週 | Network Theorizing on Contagion, Cognitive Social Structure, and Homophily |
| 第 5 週 | Social Network Data Network Analysis Lab Session I - UCINET |
| 第 6 週 | Theorizing and Analysis of Affiliation Networks |
| 第 7 週 | Network Analysis Lab Session II - UCINET |
| 第 8 週 | Proposal Presentations |
| 第 9 週 | Theorizing and Analysis of Semantic Networks |
| 第 10 週 | Network Analysis Lab Session III -R, Gephi, NodeXL |
| 第 11 週 | Analysis of Hyperlink and Representational Networks |
| 第 12 週 | Analysis of Digital Networks (interpersonal) |
| 第 13 週 | Analysis of Digital Networks (group, community) |
| 第 13 週 | Project Consultation |
| 第 15 週 | Modeling of Network Formation and Evolution |
| 第 16 週 | Writing Week |
| 第 17 週 | Fnal Presentations and Course Wrap-up |
In addition to the required textbooks listed below, students will be assigned weekly readings in the form of journal articles, which are grouped based on topical areas. Required texts ‧ Borgatti, S. P., Everett, M. G. & Johnson, J. C. (2013).?Analyzing social networks. London: Sage Publications. ‧ Hanneman, R. A. & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California, Riverside. Available online at: http://faculty.ucr.edu/~hanneman/nettext/index.html ‧ Hansen, D., Shneiderman, B., & Smith, M. A. (2010).?Analyzing social media networks with NodeXL: Insights from a connected world. Morgan Kaufmann. ‧ Monge, P. R., & Contractor, N. S. (2003).?Theories of communication networks. Oxford University Press, USA. ‧ Wasserman, S., & Faust, K. (1994).?Social network analysis: Methods and applications?(Vol. 8). Cambridge university press. Software used for lab sessions ? Gephi: Download http://gephi.org/users/download/ ? NodeXL: Download http://nodexl.codeplex.com/releases/view/117300 ? UCINET: Download http://sites.google.com/site/ucinetsoftware/downloads ? R: Download http://cran.r-project.org/bin/windows/base/ http://www.rstudio.com/products/rstudio/download/
- 地點
- HK 226
- 時間
- Monday 11:30-13:30 (or by appointment)
- 聯絡方式
- Instructor: Dr. Chih-Hui Lai (賴至慧) Email: chlai@g2.nctu.edu.tw