Course Information
Course title
Social Media and Social Network Analysis 
Semester
111-1 
Designated for
COLLEGE OF SOCIAL SCIENCES  GRADUATE INSTITUTE OF JOURNALISM  
Instructor
Adrian Rauchfleisch 
Curriculum Number
JOUR7094 
Curriculum Identity Number
342EM3100 
Class
 
Credits
3.0 
Full/Half
Yr.
Half 
Required/
Elective
Elective 
Time
Friday 7,8,9(14:20~17:20) 
Remarks
Restriction: MA students and beyond
The upper limit of the number of students: 15.
The upper limit of the number of non-majors: 5. 
 
Course introduction video
 
Table of Core Capabilities and Curriculum Planning
Table of Core Capabilities and Curriculum Planning
Course Syllabus
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Course Description

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The course introduces the analysis of social media data with a particular focus on social networking analysis. Students learn how to use the R programming language to collect, process, and analyze digital trace data in the course. The course focuses on practical examples that can also be used in data-driven journalism or business analytics. The course starts with a general introduction to R. In the second block, students learn 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 automatically via R. Students are specially prepared for the challenging work with texts (for example, regular expression). In the fourth block, the students plan their own projects. At the end of the course, some state-of-the-art methods are presented in the form of an outlook. 

Course Objective
Introduction to R
Data analysis and visualization of digital trace data
Twitter and Facebook data can be collected automatically
Learn new methods
Text mining 
Course Requirement
 
Student Workload (expected study time outside of class per week)
 
Office Hours
 
Designated reading
 
References
 
Grading
   
Progress
Week
Date
Topic
No data