Technische Universität Ilmenau

Computational Communication Research - Modultafeln of TU Ilmenau

The Modultafeln have a pure informational character. The legally binding information can be found in the corresponding Studienplan and Modulhandbuch, which are served on the pages of the course offers. Please also pay attention to this legal advice (german only). Information on place and time of the actual lectures is served in the Vorlesungsverzeichnis.

subject properties subject number 101882 - common information
subject number101882
departmentDepartment of Economic Sciences and Media
ID of group2559 (Kommunikationswissenschaft mit Schwerpunkt Computational Communication Science)
subject leaderProf. Dr. Emese Domahidi
term Wintersemester
previous knowledge and experience

Familiarity with quantitative methods in communication research. R skills are a plus, however, not mandatory.

learning outcome

Computational Communication Research: Conspiracy Theories and Group Dynamics in Social Media

Social media like Facebook, Twitter, YouTube or Reddit provide a platform for users to discuss a variety of topics with other users. However, these discussions are lately under scrutiny of leading to the distribution of conspiracy theories and the enforcement of bias such as pluralistic ignorance. While there are first studies on conspiracy theories in social media, e.g. on the topic of vaccination or chemtrails, the investigation of group dynamics across multiple discussions of conspiracy theories is still an academic void in the field.

In this course, we will have a close look at group dynamics that are present in various discussions related to conspiracy theories in social media. We will explore the phenomenon via computational methods and network analysis.

In the winter semester, students will review previous literature on conspiracy theories and group dynamics in digital media. Moreover, in order to analyze the topic students will get acquainted with relevant computational approaches of content and network analysis. On the basis of recommended readings participants will discuss findings, theoretical perspectives and applied methods. Students will work in small research groups and develop own research questions based on earlier literature. An introduction to R for Data Science is provided.

In the second part (=summer semester) students will learn to use some computational methods in a research project. First students get an introduction in R for data management and analysis. Afterwards, students will analyze the data in small research groups (with help from the supervisor) in order to answer their research questions developed in the first part.

In this course students will learn and apply computational methods in order to investigate their research questions. While there will be an introduction to these methods in the course, I strongly recommend to visit parallel the specialization module ”Introduction to Computational Communication Science” (offered by Aliya Iskenderova).


media of instruction
literature / references
evaluation of teaching


Freiwillige Evaluation:

WS 2017/18 (Seminar)

Details in major Master Medien- und Kommunikationswissenschaft/Media and Communication Science 2013
subject nameComputational Communication Research
examination number2500404
credit points10
on-campus program (h)67
self-study (h)233
Obligationobligatory elective
examalternative examination performance
details of the certificate

Students are required to conduct their own research, present the findings, and write a term paper based on their work during the two semesters (see more in the description below)

Signup details for alternative examinations


Freiwillige Evaluation:

WS 2017/18 (Seminar)

maximum number of participants20