Starting as soon as possible, our Department Computational Social Science (CSS), Team Transparent Social Analytics located in Cologne, is looking for a

Student Research Assistant

(15,20 € / 16,09 € hourly rate, up to 10 hours per week, temporary)

The department Computational Social Science (CSS) collects digital behavioral data and provides computer-based methods for collecting and analyzing such data for social science research. It also supports scientists with the integration of digital behavioral data into their research designs. The department's research focuses on the quality of digital behavioral data, the development and validation of computational social science methods and the transformation of digital societies.

The BMFTR-funded project WIEGE (“Wiederholt Getäuscht” - “Repeatedly Deceived”) investigates how repeated, cross-platform political disinformation shapes young people’s everyday media experiences and what consequences it has for their attitudes, trust, and behavior. In the Transparent Social Analytics team, we are working on working packages within WIEGE that are concerned with the automated detection of disinformation in social media data. To this end, we compare various machine learning-based methods. We also use computational methods to analyze the content of cross-platform political disinformation.

Your tasks will be:

Systematic evaluation of research literature in the fields of social sciences, computational social science, and data science
Assistance in developing pipelines for the automated detection of disinformation in large text corpora using established machine learning models and LLMs
If necessary, assistance with the manual annotation of smaller datasets

Your profile:

Enrollment in a bachelor's (advanced) or master's program in sociology, political science, communication studies, linguistics, computer science, data science, or a related discipline
Proficiency in Python, or proficiency in R with a willingness to learn Python
Proficiency in German and English
Experience in systematically analyzing extensive research literature, or a strong willingness to learn
Experience in applying natural language processing methods to large datasets, or a strong willingness to learn
Interest in addressing social science questions using computational methods (Computational Social Science)

Our Benefits:

Exciting and practical insights into an interdisciplinary research project at the intersection of the social sciences and computer science
An interdisciplinary work environment with a friendly and collegial atmosphere, as well as a wide range of opportunities to develop your professional and methodological skills, including the opportunity to write a thesis related to the project
Flexible working hours and regulations for mobile working
Very good conditions for reconciling work and family life
Holistic company health management and discounted participation in the university's sports programme
Promotion of your skills through further training measures

Contact

For further information concerning the tasks please contact Pia Schrot via E-Mail. If you have questions about the application process, please contact Christine Laßmann via E-Mail.

Interested?

Our reference number is: SHK-CSS-39