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Network Science

Network science aims to develop methods and tools for the collection, processing and analysis of relational data (e.g. from social media or sensor data) which can be modelled as a network. Network models facilitate to explain and predict the dynamics of social systems.

Our main research areas in the field of network science are:

  • Measuring face-to-face interactions via RFID sensors in various environments (e.g. academic conferences) and combining these data with survey data on behavior and personality traits
  • Networks of interactions between users of online platforms (such as Wikipedia, Reddit, Twitter), statistical modelling of patterns of online interactions (regarding information behavior, cooperation, conflict etc.)
  • Generative network models which aim to explain and predict the behavior of subpopulations, e.g. collaborations between female and male researchers
  • Cultural networks that link geographical regions through shared online preferences
  • Lietz, Haiko, Mathieu Génois, Johann Schaible, Maria Zens, and Marcos Oliveira. 2023. "Community formation at IC²S² 2017." International Conference on Computational Social Science (IC²S² 2023), Copenhagen, 2023-07-18.
  • Génois, Mathieu, Maria Zens, Marcos Oliveira, Clemens Lechner, Johann Schaible, and Markus Strohmaier. 2023. "Combining Sensors and Surveys to Study Social Interactions: A Case of Four Science Conferences." Personality Science 4: 1-24. doi:
  • Lietz, Haiko. 2022. "Identifying endogenous time to slice longitudinal network data." XLII Sunbelt International Social Network Conference, Cairns, Australia, 2022-08-30.
  • Génois, Mathieu, Maria Zens, Marcos Oliveira, and Johann Schaible. 2023. "[Poster:] Exploration of contact behaviour during scientific conferences." IC2S2 2023: International Conference on Computational Social Science, 2023-07-17.
  • Schoch, David. 2023. "signnet: An R package for analyzing signed networks." Journal of Open Source Software 8 (81): 4987. doi: