Dear colleagues,

We are happy to invite you to the fifth installment of the DiMES workshop series. 

On February 12 (Thursday) and 13 (Friday), 2026, Dr. Frank Mangold and a colleague (GESIS Leibniz Institute for the Social Sciences) will teach a two-day in-person workshop on Web Tracking: From Raw Data to Analysis (see below for a short introduction). Please note that GESIS is now collecting web tracking data as part of the GESIS Panel.dbd Digital Behavioral Data Sample, and this data will soon be made available for researchers. You can be among the first to get an in-depth introduction to this data source and how to use it for your research. Of course, the workshop will also be helpful for researchers who have collected or will collect web tracking data from other sources.  

The workshop is primarily open to PhD students, postdoctoral researchers, and faculty from FB PolSoz. Additionally, please consider inviting advanced Master's students with a particular 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 complete this form by January 23, 2026. We plan to offer up to 20 seats. If registrations exceed the limit, PhD students and postdoctoral researchers from PolSoz will be given preference, and the remaining seats will be distributed on a first-come, first-served basis. 

If you have any questions about this workshop, please reach out to Marko Bachl (marko.bachl@fu-berlin.de). We are also still interested in suggestions for workshop topics or lecturers, as we plan to organize more workshops in 2026. 

Best,

Marko & Bruno 

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Web Tracking: From Raw Data to Analysis (Two-Day Workshop)

Short Description

The Internet has profoundly reshaped everyday life and media use. Traditional self-reports reach their limits when capturing the diversity and dynamics of digital behavior. Web tracking offers a behaviorally grounded approach—especially in combination with panel surveys. At the same time, such data pose theoretical, infrastructural, ethical, and legal challenges. This workshop provides a practice-oriented introduction to preprocessing and analyzing web-tracking data, highlights typical decision points (“researcher degrees of freedom”) and best practices, and—together with participants—develops suitable research designs in Computational Communication Research. Alongside conceptual and methodological input, hands-on exercises with example datasets in R are a central focus.

Target Audience

Researchers and practitioners who use or plan to use digital behavioral data in their work (e.g., individual online exposure) and/or are interested in complex, longitudinal, and nested data structures.

Prerequisites

Confident data wrangling, linking, and transformation skills in R (tidyverse). Please bring your own laptop.

Learning Objectives

• Deepened understanding of core concepts, methods, and challenges in working with web-tracking data
• Critical reflection on analytic choices and decision spaces; introduction to robustness checks and multiverse analysis
• Practical toolchain and workflows for efficient analysis in R

Format & Schedule (Outline)

• Mix of lectures and hands-on exercises, group work, and brief project consultations
• Day 1: Potentials & core challenges; preprocessing/filtering; initial aggregation & classification; handling skewed distributions
• Day 2: Nesting & multilevel perspectives; robustness checks & sensitivity analyses; multiverse logic; applying methods to participants’ own ideas

Frank Mangold is a Senior Researcher at GESIS and the acting team lead of the Designed Digital Data team in the Computational Social Science Department. He pursued his doctoral studies at the University of Hohenheim. His research interests involve digital media environments, digital behavioral data - especially linked web tracking and survey data - as well as statistical modeling (e.g., multilevel modeling, structural equation modeling, item response theory). More specifically, Frank's work focuses on audience structures and news media repertoires, media behaviors and media-related dispositions, opinion leadership and communication networks, among other topics. Frank’s research has been published in a variety of national and international peer-reviewed journals, including Journal of Communication, American Political Science Review, Proceedings of the National Academy of Sciences (PNAS), New Media & Society, and Communication Methods & Measures.