Kies de Nederlandse taal
Course module: 800861-M-3
Research Skills: Social Media Analytics
Course info
Course module800861-M-3
Credits (ECTS)3
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Humanities and Digital Sciences; TSHD: Commun. and Inform. Sciences; TSHD: Department Communication and Cognition;
Is part of
M Communication and Information Sciences
M Linguistics and Communication Sciences (research)
Convenant TSH
dr. A.P. Schouten
Other course modules lecturer
Academic year2019
Starting block
Course mode
Registration openfrom 14/10/2019 up to and including 24/01/2020
After completion of this course, students…
  • understand the pros and cons of social media data;
  • can work with several tools to collect and analyze social media data;
  • understand the basics of search engine optimization and search engine advertising;
  • can work with Google Analytics;
  • are able to collect, analyze, and report social network data;
  • can report, visualize, and discuss social media data.
Online and social media data is increasingly used for both academic and non-academic research. Organizations monitor and analyze internet and social media data to manage their online strategies, to assess the success of their website to optimize their website design, and to discover consumer trends. In academia, we increasingly make use of social media data to study the spread of information through networks, to study online impression formation, to investigate consumer behavior, amongst others.

In this course, we discuss the basics of social media and web analytics from a communications perspective. The course consists of three parts. First, we discuss the pros and cons of social media data and we will learn to use several tools to collect and analyze social media data. In the second part, we will learn the basics of search engine optimization and search engine advertising and you will learn to analyze website traffic using Google Analytics. The third part of the course focuses on collecting and analyzing social network data. You learn the basics of social network analysis and will learn to use Gephi to analyze social network data.

The course will consist of 7 small-group lectures. In the lectures, you will work with several social media analytics tools, so you’ll need to bring your laptop with you to class with the appropriate software installed. You will also need to use this software to make some of the assignments. During the course, you will work on a social media analytics project with a small group of students. The goals of the project are (1) to use the skills learned in the lectures to conduct your own social media research, and (2) to learn how to report, visualize and discuss social media data. Moreover, each of the three parts of the course will be assessed with an individual assignment.

This course will help you in your professional development in the following ways. First, social media and web analytics are a useful skill and often a requirement for a professional career in (online) marketing. Second, you learn analytic skills and specific software programs that are commonly used in organizations. Third, people who can bridge the gap between data analytics and business goals are few and far between. It is a very worthwhile skill to be able to advice organizations on how to best use social media analytics to attain their business goals.

Assessment of the course is based on your grade for the individual assignments and the group project. The final course grades will consist of your grade for the group project (40%), and the at-home and in-class assignments (60%).

NB. This course will be taught in English. This means that all course material is in English and that you will be required to hand in all assignments in English as well.
NB. You cannot take this course if you have already taken the Social Media Analytics Course in the bachelor (880061).
Contact person
dr. A.P. Schouten
Timetable information
Research Skills: Social Media Analytics
Required materials
Recommended materials
Selection of articles and chapters that will be announced on Canvas.
Group Project

Individual Assignments

Final Result

Kies de Nederlandse taal