Author: Diana Ignatovich

Workshop Recap: Introduction to Git

Diana Ignatovich

On February 6th, 2025, LK Seiling facilitated a workshop for an Introduction to Git, with support from Sascha Kostadinoski and Quentin Bukold. This was co-organized by the Methods Lab and took place at the Weizenbaum institute. The hybrid event provided a thorough overview on the foundation of Git and its relative platforms for about 30 participants. 

Firstly, Git was introduced for its general relevance. Seiling explored the qualities of its version control system and the advantages of efficiently managing changes to files. Its widespread use and accessibility were also highlighted by the software’s free and open source application. At its core, Git enables collaborative work by allowing concurrent adjustments to files by multiple participants and offers a system to track the changes made without requiring alterations to the original file.

LK Seiling describes the features of Git

Next, participants were invited to open the Terminal and guided through some basic commands. To this end, commands for traversing directories, creating, moving, organizing, and deleting files were explained and demonstrated in detail.

This was followed by instructions on the key functionality of Git, such as the Git repository, Git commands, branches, and conflict resolution. For instance, the branches gave insight into how to leverage simultaneous work done separately from the overall code base. This is especially beneficial for feature development while also helping to streamline the process of reviewing changes before merging. Throughout this instruction, commands were given to switch branches and merge scripts in the terminal, which was operationalized with a quickly constructed example. Seiling also provided necessary information on managing repositories, including visuals of the basic workflow and linkage between local and remote repositories, either for individual or collaborative effort.

For those curious when to use which Git platform, Bukold jumped in to detail the major differences between Github, Gitlab and Git.

In the second hour of the workshop, Seiling encouraged participants to implement these basics by imagining the context of a classic Python project, one that might require collaborative engagement. Here, Python scripts were saved, renamed and staged accordingly to git messages and configurations. The principle git practices were emphasized to remind the audience of when and how to commit changes to the previously specified local repository. Furthermore, Seiling prepared guests to make requests when merging work, added description templates for joint projects and generally taught the features of use for group collaboration. 

LK Seiling explains how to stage and commit changes

Later, Seiling explored some advantageous elements of the GitLab platform, accessible free of charge to Weizenbaum researchers, by describing the repository graph, issue tracking and project management tools. To elaborate, the repository graph structures insight into how a participant makes a contribution or change by arranging branches to show merges or commits, particularly relevant for collaborative code projects. In case of software malfunctioning, the issue tracking feature allows one to see who is working on what branch for an update on the progress of the problem. Finally, Gitlab’s management tool was outlined for instances of assigning work, applying tags to notify when projects are finished and to open or close potential issues. 

To close, Kostadinoski briefly summarized the basic elements of Git, along with its implications in data work, such as for software development and research. He simplified key terms and embraced questions in a Q&A. Seiling joined in, encouraging participants to “learn by doing” and stay connected with each other via Weizenbaum associated Github accounts for future internal coordination. 

Throughout this workshop, participants were presented with various tasks and benefited from frequent recaps that highlighted key points, ensuring a solid understanding of the material. Attendees both online and in person freely asked questions and received support from instructors. Therefore the Methods Lab would like to give a huge thank you to LK Seiling, Sascha Kostadinoski and Quentin Bukold for their clear instruction on the foundations of Git and for facilitating such an engaging environment for all participants. 

Workshop: Social Science and Language Models (April 3–4, 2025)

Methods Lab

The Methods Lab with contributors Zeerak Talat and Flor Miriam Plaza del Arco are excited to introduce the workshop “Social Science and Language Models – Methods and theory to responsible research on and with Language Technologies” taking place on April 3–4, 2025 at the Weizenbaum Institute. This hybrid event encourages interdisciplinary collaboration to promote ethically responsible research in the application of natural language technology. As methodology utilizing language models is increasingly applied to a variety of contexts from social science, health-care settings to computer software development, research suggests the growing need to monitor potential biased outcomes of its use. However, the absence of collaborative understanding between researchers of social science and those in Natural Language Processing (NLP), perpetuates discrimination as biases in the conception and measurement of socio-technical systems often go unrecognized.


Therefore we hope to engage a diverse group of researchers involved in the methodology of social or economic fields of discipline to address this prejudice in language technologies. Submissions of abstracts are encouraged to involve aspects of bias in the mitigation and measurement of NLP, as well as its implications in the social sciences.


For more information, visit our program page. We are looking forward to your participation!

Spotlight: The Data Workers’ Inquiry 

Diana Ignatovich

AI applications are growing in popularity, everyday digital tasks are intuitively streamlined, and social media platforms are flooded with automated media that emulate the clarity of actual events. Naturally, this inspires discussions of future opportunities and concerns, such as the possibility of computers overtaking jobs that once relied upon humans. But amidst this consideration of AI into our routine behaviors, how much do we really know about the foundation of these tools? What are the invisible costs of this innovation, and who bears the consequences? The answer is revealed in this article, unsettling accounts behind the scenes of our usage are presented by the data workers’ inquiry.

This community-based initiative fights for fair working conditions and adequate recognition of data workers’ expertise. Since 2022, workers behind AI applications have been investigating their own workplaces to address labor conditions and build workplace power. Derived from the principles of 1880s Marxist thinking, workers conduct research tailored to their political and environmental concerns, with support from trained qualitative researchers. This team of researchers includes lead researcher Milagros Miceli with the Weizenbaum Institute, Adio Dinika, Krystal Kauffman, Camilla Salim Wagner, and Laurenz Sachenbacher. Without compromising the workers’ epistemic authority, they provide training in methods for data collection and analysis to create a methodology for workers to use within investigations. They also diligently monitor ethical and legal boundaries throughout the duration of projects. 

The inquiries take place across Venezuela, Kenya, Syria and Germany. Whether in essays, artwork or documentaries, data workers creatively share their perspective working under various AI industries. The striking truths are outlined in the inquiries below. Ultimately, this research will provide structure for collective action, establishing future ethical guidelines in regard to the treatment of data workers. 

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Special Issue: Open Research Infrastructures and Resources for Communication and Media Studies

Diana Ignatovich

Despite the advantages of accessible and reproducible research practices for scholars in media and communication research, few journals present opportunities to examine these resources. Therefore the journal of Media and Communication plans to publish a Special Issue on “Open Research Infrastructures and Resources for Communication and Media Studies” in 2026 to encourage an exchange of feedback between researchers on the implications of relevant resources and infrastructures. The Call for Papers on this issue invites papers to discuss and pursue resources that adhere to open science principles. The Methods Lab lead, Christian Strippel is a co-editor of this issue. 

In regards to submissions, open science principles emphasize non-commercial tools that may apply to both quantitative and qualitative methods. Articles that present datasets, evaluate research software or compare instruments involved in data analysis are encouraged. The scope also extends to papers discussing developments or challenges to the operation of open research infrastructure, and investigates the potential areas for improvement. Notably, this publication considers implications for researchers of different socioeconomic and cultural backgrounds to address research inequalities and promote sustainability. Thus, papers are encouraged to reflect this dimension of diversity. In conclusion, contributions to this publication equip researchers with greater access and ease of operation to these valuable resources, ultimately advancing and promoting inclusivity within open research practices. 

Submission of Abstracts: 1-15 September 2025

Submission of Full Papers: 15-31 January 2026

Publication of the Issue: July/December 2026

New preprint article: Extracting smartphone use from Android event log data

Diana Ignatovich

With smartphones now more prevalent in everyday life than ever before, understanding their use and its implications becomes increasingly necessary. While self-reporting in surveys is the method typically used to assess smartphone use, it is affected by various problems such as distorted retrospection, social desirability bias, and high aggregation. More advanced methods include the Experience Sampling Method (ESM), which presents multiple short surveys per day to limit the degree of retrospection, and logging (Android only), which accesses an internal log on the device itself that documents each user activity in extremely high resolution. Although the latter is the most precise and objective method available for assessing smartphone use, the raw data received from the log file requires extensive transformation to extract actual human behavior rather than technical artifacts. Still, this transformation was never documented systematically and researchers working with this input implemented arbitrary steps to extract the data they required. 

The preprint article Extracting Meaningful Measures of Smartphone Usage from Android Event Log Data: A Methodological Primer, authored by former Methods Lab fellow Douglas Parry and Methods Lab member Roland Toth, aims to provide a detailed step-by-step guide to extracting different levels of smartphone use from Android log data. Specifically, the guide helps identify glances (short checks without unlocking the device), sessions (uses from unlocking to locking), and episodes (single app uses) from such log files, allowing for further investigation. All steps are presented as pseudo-code as well as described in text. In addition, the Online Supplementary Material (OSM) contains the full pseudo-code, a rendition in the R programming language, a sample data set containing raw log data, and more helpful material.

This guide ultimately enhances our understanding of how humans interact with these versatile devices, particularly beneficial for projects within the social sciences and neighboring disciplines. While survey methods are recognized for their economical advantages and ease of administration, access to objective high-resolution data contributes a more refined perspective. We hope this article helps researchers identify valuable measures from raw android event log data, thereby making this rich data source more accessible and manageable than it has previously been.