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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
Name Department Team Email Telephone
  • Schoch, David. 2023. "signnet: An R package for analyzing signed networks." Journal of Open Source Software 8 (81): 4987. doi: https://doi.org/10.21105/joss.04987.
  • Ferrara, Antonio, Lisette Espín Noboa, Fariba Karimi, and Claudia Wagner. 2022. "Link recommendations: Their impact on network structure and minorities." In WebSci '22: 14th ACM Web Science Conference 2022, 228-238. New York: Association for Computing Machinery. doi: https://doi.org/10.1145/3501247.3531583.
  • Bacaksizlar Turbic, N. Gizem, Melih Can Yardi, Ozgem Elif Acar, Oguz Gurerk, Ali Hurriyetoglu, Tolga Etgu, and Erdem Yoruk. 2022. "Social Networks in Times of Turkey’s Currency Crisis." The 11th International Conference on Complex Networks and their Applications (Palermo, Italy), 2022-11-08.
  • Martins Rosa, Jorge, N. Gizem Bacaksizlar Turbic, Alda Magalhães Telles, Clara González Tosat, Cristian Jiménez Ruiz, Kalliopi Moraiti, Özgür Karadeniz, and Valentina Pallacci. 2022. "Exploring User Engagement with Portuguese Political Party Pages on Facebook: Data Sprint as Workflow." Dígitos. Revista de Comunicación Digital 8 127-154. doi: https://doi.org/10.7203/drdcd.v1i8.233.
  • Schoch, David. 2022. "Mathematical Foundations of Network Centrality." Seminar Series at Network Science and Social Network Analysis group, University of Utah, 2022-08-12.