Analyzing Digital Behavioral Data

Social media data and other digital behavioral data (DBD) are important for analyzing social science topics in digital societies and for understanding the evolvement of socio-technical systems. GESIS offers methodological insights on how computational methods support social science research and off-the-shelf tools for mining social entities, enriching data and disclosing social structures. With GESIS Notebooks we also provide an infrastructure for reproducible research and for sharing computational tools in this area. The "Total Error Framework for Digital Traces of Human Behavior on Online Platforms" (TED-On) is our first step in building a comprehensive framework for systematic error detection in the collection, processing, and analysis of digital behavioral data. 

TED-On

Methodology, Framework 

GESIS aims at providing a comprehensive framework for systematic error detection in the collection, processing, and analysis of digital behavioral data. With focus on social media data, we developed the Total Error Framework for Digital Traces of Human Behavior on Online Platforms (TED-On).

Paper | Video | Tutorial | Slides

Gender Inference

Methods Insight

We provide an overview of state of the art methods for inferring gender from individual's names and/or images – along with easy to follow instructions on how to use the different methods, directly executable demo notebooks for trying them out and a short guideline for responsible usage.

Methods Insight Paper

GESIS Notebooks

Virtual Research Infrastructure

Explore GESIS Notebooks (beta) – 
we are building an online environment for web based large-scale data analysis with software suits for coding languages like R or Python, and including services for application, publication, and archiving. Try GESIS Notebooks for making your own Binder repository available. 

GESIS Notebooks

HypTrails

Tool

The HypTrails Framework allows comparisons of hypotheses about sequential behavior – examples for this are, how websites are navigated or how persons move through cities.

Tutorial | Code | Paper | Paper |
Paper

Social Media Monitoring

Tool

Try this tool to explore the Twitter and Facebook data of German politicians and political organizations GESIS has collected around the federal elections 2013 and 2017.

Tool | 2013 Data | 2017 Data |
2013 Report | 2017 Report | 
Paper

WikiWho

API, Tool

Use the WikiWho Tool for 'social' text mining and analyze editing and revising transactions of Wikipedia entries across languages. Data can be downloaded as data set or obtained via an API.

WikiWho API | Data | WikiWho Wrapper | Report | Tutorial 

Open Science

We support and implement
Open Science.

Please visit our work
on GitHub.

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