GESIS is a research-based infrastructure institution for the social sciences and conducts its own continuous and interdisciplinary research in four major research areas. The results of our research serve both to gain scientific knowledge and to sustainably improve our offerings for the social sciences.
For GESIS, the quality of data takes center stage. GESIS strives to provide high-quality research data as well as methods and tools that enable users to assess for themselves how high the quality of research data is. The research focus is therefore also geared towards this core interest. In order to contribute to the generation of knowledge about data quality, GESIS focuses on the research areas of survey methodology, computer-based methods and research data management. Together, we focus our methodologically oriented research on supporting researchers who work with quantitative data.
Sun, Jun, and Fariba Karimi. 2024. "Emergence of group size disparity in growing networks with adoption." Communications Physics 7 (19 September 2024): 309. doi: https://doi.org/10.1038/s42005-024-01799-z.
Dahou, Abdelhalim Hafedh, and Brigitte Mathiak. 2024 (Forthcoming). "Automatic Categorization of Software Repository Domains with Minimal Resources."
Ferrara, Antonio, Francesco Bonchi, Francesco Fabbri, Fariba Karimi, and Claudia Wagner. 2024. "Bias-aware ranking from pairwise comparisons." Data Mining and Knowledge Discovery 38 (4): 2062-2086. doi: https://doi.org/10.1007/s10618-024-01024-z.
Ell, Theresia, Lydia Repke, and Henning Silber. 2024. "Personal and Technology-Based Communication and Its Impact on Mental Health From a Network Perspective." Sunbelt Conference 2024, Heriot-Watt University, Edinburgh, 2024-06-24.
Melchior, Alice, Sebastian Schongen, and Reinhard Pollak. 2024. "Mixed-Method Approaches to Capture Digitalisation. The Case of Networked Digital Technology Permeation in German Hospitals." In Digitalisierung der Arbeitswelten, edited by Sabine Pfeiffer, Manuel Nicklich, Michael Henke, Martin Krzywdzinski, Martina Heßler, and Ingo Schulz-Schaeffer, 531-555. Springer VS, Wiesbaden. doi: https://doi.org/10.1007/978-3-658-44458-7_24.
Burger, Axel. 2024. "Predictors and implications of mixed feelings during electoral campaigns." 29. Tagung der Deutschen Vereinigung für Politikwissenschaft (DVPW), Georg-August-Universität Göttingen, 2024-09-27.
Sun, Jun, and Fariba Karimi. 2024. "Emergence of group size disparity in growing networks with adoption." Communications Physics 7 (19 September 2024): 309. doi: https://doi.org/10.1038/s42005-024-01799-z.
