Digital Behavioral Data

Your Research Infrastructure for Digital Behavioral Data

We are building a continuously evolving and comprehensive digital behavioral research infrastructure based on our established services and our recognized expertise. Our goal is to support you with know-how, methods, and data, so that your research can harvest the full potential of new data.

Digital behavioral data are a methodological innovation with great potential for the social sciences. They can supplement experimental and survey-based research and allow researchers to investigate known and emerging social phenomena with innovative methods. However, these new data and methods also bring about significant challenges for researchers.
GESIS provides support for social scientists

  • to collect,
  • to process,
  • to analyze
  • and archive
  • as well as to evaluate and optimize data quality.
Tools to analyze DBD
DBD for Scientific Use

GESIS sustains the formation of an interdisciplinary community in the field of Computational Social Science (CSS) by organizing a summer school on methods in CSS and by offering further training courses in data science and CSS methods. Our conferences and symposia provide for tutorials and hands-on-workshops. The GESIS Computational Social Science (CSS) Seminar is a monthly event for expert exchange on data science and social analytics (conducted in English).

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We provide computer code and tutorials to handle DBD:

 

We collect content and social interactions from online social media:

 

Our services to collect and analyze DBD are based on approaches from text and data mining, and network analysis.

  • Text and data mining comprises the development and application of methods which are designed to extract knowledge that is relevant to the social sciences from unstructured texts or data streams.
  • 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.