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. 2020. "Drawing impossible boundaries: Field delineation of Social Network Science." Scientometrics 125 2841–2876. doi: https://doi.org/10.1007/s11192-020-03527-0.
- Weller, Katrin. 2018. "International Conference on Web and Social Media (ICWSM 18)." Anzahl: 3.
- Weller, Katrin. 2018. "International Conference on Computational Social Science (IC2S2)." Anzahl: 4.
- Génois, Mathieu. 2018. "NetSci." Anzahl: 12.
- Génois, Mathieu. 2018. "EPJ Data Science." Anzahl: 2.