Computational Communication Research - Modultafeln of TU Ilmenau
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|subject properties subject number 101882 - common information|
|department||Department of Economic Sciences and Media|
|ID of group||2559 (Kommunikationswissenschaft mit Schwerpunkt Computational Communication Science)|
|subject leader||Prof. Dr. Emese Domahidi|
|previous knowledge and experience|
Familiarity with quantitative methods in communication research. R skills are a plus, however, not mandatory.
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|
WS 2017/18 (Seminar)
|Details in major Master Medien- und Kommunikationswissenschaft/Media and Communication Science 2013|
|subject name||Computational Communication Research|
|on-campus program (h)||67|
|exam||alternative 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|
WS 2017/18 (Seminar)
|maximum number of participants||20|