課程資訊
課程名稱
社群媒體與社會網絡分析
Social Media and Social Network Analysis 
開課學期
107-1 
授課對象
社會科學院  新聞研究所  
授課教師
劉好迪 
課號
JOUR7094 
課程識別碼
342EM3100 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期一7,8,9(14:20~17:20) 
上課地點
新聞401 
備註
本課程以英語授課。
限學士班四年級以上
總人數上限:20人 
課程簡介影片
 
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課程概述


The course gives an introduction to the analysis of social media data with a particular focus on social networking analysis. In the course, students learn how to use the R programming language to collect, process and analyze digital trace data. The course focuses on practical examples that can also be used in data-driven journalism. The course starts with a general introduction to R. In a second block, students learn how to read data, perform statistical procedures, and visualize results in high-quality plots. In the third block, students learn how to collect data from Twitter or Facebook automatically via R. Students are specially prepared for the challenging work with texts (for example, regular expression). In a fourth block, the students plan their own project. At the end of the seminar, some state-of-the-art methods are presented in the form of an outlook.
 

課程目標

Introduction to R
Data analysis and visualization of digital trace data
Twitter and Facebook data can be collected automatically
Learn new methods
Text mining
 
課程要求

WEEK TOPIC DETAILS
INTRODUCTION

1 What are social media? Which platforms can be analyzed? Installation of R and R Studio. Packages for the course are installed.

2 How to use R? R-syntax in self-study: http://tryr.codeschool.com/ The most important objects in R are presented. What are functions and how to use them?
WORKING WITH DIGITAL TRACE DATA

3 Analyze data What is an API? How to download digital trace data?

4 Visualize data How to work with ggplot2? What is vector graphics?

5 Collect and analyze Twitter Data How to collect and transform digital trace data.

6 Introduction social network analysis Social network analysis in theory and practice

7 Presentations

8 Twitter network analysis How do I analyze social networks? How do I export this data? Learn Regex.

9 Work with Gephi How to analyze data in Gephi and import the results into R?

10 Brainstorming Short elevator pitch from each group

11 Text mining How can I save and edit documents in R? What is sentiment analysis?

12 Group meetings We plan the data analysis

13 Other social media How can I download data from other platforms such as Wikipedia and Facebook?

14 Field phase Individual group meetings

15 Field phase Individual group meetings

16 Final team meeting Last Review: Discuss first results

17 Presentation of the projects Every group presents their project

18 Review and evaluation


 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
 
參考書目
指定閱讀
Arlt, D., Rauchfleisch, A., & Schafer, M.S. (forthcoming): Polarization or dialogue? Political debate on Twitter in the wake of the Swiss referendum on the Nuclear Withdrawal Initiative. Environmental Communication.
Ausserhofer, J., & Maireder, A. (2013). NATIONAL POLITICS ON TWITTER. Information, Communication & Society, 16(3), 291–314. doi:10.1080/1369118X.2012.756050
Chang, W. (2013). R graphics cookbook (First edition). Beijing, Cambridge, Farnham, Koln, Sebastopol, Tokyo: O'Reilly.
Easley, D., & Kleinberg, J. (2010). Networks, crowds and markets: Reasoning about a highly connected world. Cambridge: Cambridge Univ. Press.
Kaiser, J., Rhomberg, M., Maireder, A., & Schlogl, S. (2016). Energiewende?s Lone Warriors: A Hyperlink Network Analysis of the German Energy Transition Discourse. Media and Communication, 4(4), 18. doi:10.17645/mac.v4i4.554
Maireder, A., & Schlogl, S. (2014). 24 hours of an #outcry: The networked publics of a sociopolitical debate. European Journal of Communication, 29(6), 687–702. doi:10.1177/0267323114545710
Maireder, A., Weeks, B. E., Gil de Zuniga, Homero, & Schlogl, S. (2016). Big Data and Political Social Networks. Social Science Computer Review, 35(1), 126–141. doi:10.1177/0894439315617262
Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, tidy, transform, visualize, and model data. s.l.: O'Reilly UK Ltd. 
評量方式
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