Computational methods open up new research opportunities
At GESIS we conduct basic and applied research in the field of survey methodology. Our survey research is divided into the focus areas of survey statistics, survey instruments, survey operations, and comparative surveys. We pursue the goal of gaining evidence-based insights into how surveys and their data quality can be optimized. Within the framework of systematic reviews and meta-analyses, we evaluate existing research and identify research gaps. In the research area of survey methodology, we also explore the connection of survey data with digital behavioral data (e.g., social media profiles, smartphone usage data, or browsing histories) and examine how these data types can be complemented and combined. To this end, we are also driving the transfer of established concepts for assessing the data quality of surveys to digital behavioral data.
Data Quality
We conduct research to improve the quality, analytical potential, findability, and usability of research data.
To improve the quality, analytical potential, findability, and usability of research data, we conduct research on computer science methods in the fields of Natural Language Processing, Data and Network Science, Information Retrieval, and Human Computer Interaction.
Human Information Interaction & Information Retrieval
Research in the field of Human Information Interaction and Information Retrieval is concerned with how people search for, find, and use information – and how they can be better supported in doing so.
Data Science & Natural Language Processing (NLP)
Our research objective in the field of Data Science and Natural Language Processing (NLP) is the development of innovative methods and tools for the collection, utilization, processing, and analysis of research data.