Please note that due to the current situation, participation in our on-site training events is restricted. You can find further information here.
Using Social Media Data for Research: Potentials and Pitfalls (Online Workshop!)
Indira Sen, Katrin Weller
Date: 09.11 - 10.11.2020 ics-file
Location: Online via Zoom / Course language: English
The activities and interactions of hundreds of millions of people worldwide are recorded as digital traces including social media data. These data offer increasingly comprehensive pictures of both individuals and groups on different platforms, but also allow inferences about broader target populations beyond those platforms. Notwithstanding the many advantages, studying the errors that can occur when digital traces are used to learn about humans and social phenomena is essential. Incidentally, many similar errors also affect survey estimates, which survey designers have been addressing for decades using error conceptualization frameworks, most notably the Total Survey Error Framework (TSE).
In this tutorial, we will introduce the audience to the concepts and guidelines of the TSE and how they are applied by survey practitioners in the social sciences, guided by our interdisciplinary background and experience. Having understood the 'total error' perspective towards surveys, we will introduce our own conceptual framework to diagnose, understand, and avoid errors that may occur in studies that are based on digital traces of humans.
To help understand the utility of the error framework for digital traces, we apply it to diagnose and document errors in existing computational social science studies such as Understanding Political Opinion using Twitter and Using Search Queries for Inferring Health Statistics.
We also ask participants to apply the error framework to hypothetical scenarios utilizing novel forms of digital traces like mobility data as well as their own area of research, using social media datasets openly available on the web.
Survey Methodology, Computational Social Science, Digital Traces, Representativeness, Measurement Errors
Participants will hence gain insights on
- how to translate the recommendations of the TSE to a digital trace setting
- how to critically reflect on research design in social media or web data based studies
- how to systematically spot and document errors in their studies
Open to people of different disciplines but primarily aimed at those
- who have some prior experience in survey research and want to extend their knowledge on how digital behavioral data might be suitable additional data sources for their research questions
- who have already worked with digital behavioral data and want to learn about additional possibilities to critically reflect on research designs and their limitations.