Dear colleagues,

We are happy to invite you to the second instalment of the DiMES (Digital Methods and Empirical Social Science Center) workshop series.

On April 9-11 (Wednesday to Friday), 2025, Dr. Aleksandra Urman (University of Zurich) will teach a three-day in-person workshop on Algorithm Auditing for Social Science Research (see below for a short overview). The workshop is primarily open to the PhD students, postdocs, and faculty of FB PolSoz. In addition, please consider inviting advanced students with a specific interest in the topic.

The workshop is funded by DiMES and offered free of cost to participants. However, we do require reliable registration to plan the workshop. To register, please fill out this form by April 1st, 2025. We plan to offer up to 20 seats. If registrations exceed the limit, PolSoz PhD students and postdocs will be given preference, and the remainder of the seats will distributed first-come, first-serve.

If you have any questions about this workshop, please reach out to Bruno Castanho Silva (b.paula.castanho.e.silva@fu-berlin.de). We are also interested in suggestions for workshop topics or lecturers, as we plan to organize about three more workshops in 2025.

 

Overview

This 3-day workshop is meant to introduce social science researchers to the methodology of algorithm auditing - evaluation of closed-source algorithmic systems with the aim to shed light either into the way they work (functionality auditing) or the quality and fairness of their outputs (impact auditing). 

This methodology allows us to answer questions such as: are search or social media politically biased? How are gender and racial biases manifested in search results or in the outputs of generative AI chatbots? Do recommendation algorithms on LinkedIn foster gender inequality? And many others.

The workshop will consist of three parts: advanced web scraping techniques; overview of the auditing field and specific methodological approaches; hands-on small-scale auditing project. After the workshop participants will have sufficient familiarity with the auditing methodology to design and implement their own auditing studies.

The workshop is aimed primarily at social science researchers with affinity for computational methods and/or at computer science researchers with an interest in social science-relevant research questions. The participants should have familiarity with R/Python and basic web scraping techniques (e.g., scraping static webpages). There will be a short web scraping refresher on the first day, but the workshop will primarily focus on more advanced techniques (scraping dynamic webpages, handling login and captchas, using proxies, etc).

 

Dr. Aleksandra Urman is a computational social scientist specializing in the societal impact of technology. Her research lies at the intersection of social science and computer science, and examines algorithmic biases, information inequality, and online political communication using computational approaches. In the context of algorithm auditing, Aleksandra has both theoretical expertise and extensive hands-on experience implementing algorithm audits across various online platforms, with a primary focus on search engines, social media and generative AI chatbots.