PhD position for Social Networks and Digital Cultural Consumption
We are an interdisciplinary lab studying social and behavioral phenomena using network concepts. Members of the lab actively develop theories, methods and software in a variety of domains, for our own empirical studies and for our collaborative endeavors across multiple discplines. The group of Prof. Christoph Stadtfeld is looking for a motivated PhD student interested in combining social network research with analysis of digital trace data in the domain of music tastes and cultural consumption.
Sociologists have long been interested in how society affects individuals' cultural tastes. Today, it is possible to measure cultural consumption (e.g., which songs individuals listen to throughout their days) on a fine-grained level using data from online platforms and methods brought forward by the emerging discipline of computational social science. This project explores two key questions in cultural sociology with a contemporary and computational lens. First, it examines how individuals develop and maintain their cultural preferences on digital platforms and the impact of recommender algorithms on these preferences (alongside their societal implications such as data privacy and ownership, algorithm fairness, etc.). Second, it aims to bring in methodological innovations needed to combine digital data (i.e., behavioral traces on various platforms) with traditional surveys and model the longitudinal dynamics of cultural tastes and social networks from these sources.
During this project, you will be at the forefront of social network research, both independently and as a member of our research team. Your responsibilities may encompass:
- Revisiting and further developing theories from the field of cultural sociology.
- Being involved in conceptualizing and designing innovative data collection strategies and behavioral experiments.
- Developing new statistical methods for analyzing digital data with network concepts (with the potential to collaborate with other team members).
- Engaging in interdisciplinary dialogues (e.g., computer science, information science, political science, sociology, etc.) to enhance our knowledge on how digital systems shape and mediate individual preferences and their societal implications.
- Presenting research progress at related conferences to an international, multidisciplinary audience.
Successful candidates should have the following qualifications:
- An excellent Master's degree in social, computational, statistical, or behavioral sciences (e.g., sociology, applied math, economics, statistics, social data science, political science, psychology).
- Prior work such as a Master thesis that demonstrates a strong interest in quantitative social network research.
- Demonstrated experience in research design and project implementation (e.g., obervational data collection, experiment design and implementation, etc.), ideally in the domain of social networks and/or computational social sciences.
- Solid quantitative analysis and data management skills, including experience in or willingness to learn R or Python.
- Strong skills in scientific writing.
- Ability and willingness to work productively in an interdisciplinary, international team.
The PhD project may start on October 1 2024 or on a mutually agreed upon date thereafter.
We offer an inspiring research environment at one of the world's top universities, close collaboration in a small research lab that is part of a leading international network of social networks researchers, advanced training in modern social networks research, generous research funding and a competitive salary. Tuition fees do not apply.
We cultivate a collegial and supportive work environment. Weekly group meetings and regular presentations provide a forum to share problems and challenges, half-baked ideas, work in progress, and obtain peer feedback. We have regular team activities, including reading group meetings, writing retreats, and day trips, to foster collaboration, team bonding, and enrich our research experience.
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