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, Andreas Schmitz, and Johann Schaible. 2021. "Analyse sozialer Netzwerke mit digitalen Verhaltensdaten." easy_social_sciences 66 90-98. doi: https://doi.org/10.15464/easy.2021.010.
- Lietz, Haiko, Andreas Schmitz, and Johann Schaible. 2021. "Social network analysis with digital behavioral data." easy_social_sciences 66 41-48. doi: https://doi.org/10.15464/easy.2021.005.
- Schaible, Johann, Marcos Oliveira, Maria Zens, and Mathieu Génois. 2022. "Sensing Close-Range Proximity for Studying Face-to-Face Interaction." 1. In Handbook of Computational Social Science; Vol 1: Theory, Case Studies and Ethics, edited by Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu, and Lars Lyberg, European Association of Methodology series, 219-239. Abingdon, Oxon: Routledge.
- Bacaksizlar, N. Gizem. 2019. Understanding Social Movements through Simulations of Anger Contagion in Social Media. https://repository.charlotte.edu//islandora/object/etd:1406.
- Zloch, Matthäus, Maribel Acosta, Daniel Hienert, Stefan Conrad, and Stefan Dietze. 2021. "Characterizing RDF graphs through graph-based measures – framework and assessment." Semantic Web 12 (5): 789-812. doi: https://doi.org/10.3233/SW-200409.