❗️📢 Tue, Apr 28, 10:00-11:00 CET
📍 A 231 and ZOOM
Mannheim Research Colloquium on Survey Methods
#MaRCS
with

Henning Silber, @umich.edu

"Why People (Don’t) Participate in Surveys:
Evidence from Multiple Studies and Population"

👉 www.mzes.uni-mannheim.de/en/news/even...
1/2

a nonprob college fraternity panel called brolific

Survey Recruitment on LinkedIn: A Step-by-Step Guide to Targeted Outreach March 25, 2026 31 min read tutorials [Zaza Zindel Lisa de Vries] LinkedIn’s professional user base and precise targeting capabilities present social science researchers with a valuable opportunity to recruit survey participants from highly specific populations, particularly those relevant to research on employment and industry dynamics. While platforms such as Facebook and Instagram are commonly used for recruitment of survey participants, LinkedIn’s potential in survey participant recruitment remains underutilized. Its professional focus, career-centric context, and only minimal off-topic content make it ideal for reaching the potential labor force population. This is particularly relevant for studies requiring insights from specific industries, occupations, or education levels. In this Methods Bites Tutorial, Dr. Zaza Zindel (German Centre for Integration and Migration Research (DeZIM)) and Dr. Lisa de Vries (FernUniversität in Hagen) provide a step-by-step guide on how to use LinkedIn ads to recruit participants for survey research. Continue reading Social media Survey data Data collection

🆕 Content alert on Methods Bites

▶️ "Survey Recruitment on LinkedIn: A Step-by-Step Guide to Targeted Outreach"

👤 Zaza Zindel (DeZIM) & Lisa de Vries (FernUniversität Hagen)

🔗 Blogpost: socialsciencedatalab.mzes.uni-mannheim.de/article/link...

2026-04-22 | Input talk | Leah von der Heyde (GESIS) AIn't Nothing But a Survey? Using Large Language Models for Coding Open-Ended Survey Responses Hybrid event [A5, 6, Room A231 + Zoom] April 22, 2026, 13:45-15:15 Abstract Large language models (LLMs) have the potential to make survey research more efficient, including the classification of open-ended survey responses. However, as most existing research on this topic has focused on English-language text or single LLMs, it is unclear whether their applicability generalizes and how the quality of classifications compares to established methods. In this talk, I will demonstrate how LLMs can be used for coding open-ended responses using different access options and prompting and fine-tuning techniques. I will present a study testing these approaches on a dataset of German open-ended survey responses, comparing several LLMs to human coders and other automated methods. Finally, I will discuss the implications of the study findings for practitioners, including the many trade-offs researchers need to consider. Presenter(s) Leah von der Heyde is a computational social scientist and survey methodologist. Her research focuses on the potential and pitfalls of new data sources, such as large language models, for improving the measurement and representation of public opinion. Substantively, she is particularly interested in political attitudes and voting behavior. Leah received her PhD in Social Data Science and Research Methodology from the University of Mannheim. She has a background in political science from LMU Munich, the University of Mannheim, and Georgetown University. Previously, Leah was part of the Social Data Science and AI Lab at LMU Munich, worked for the European Social Survey at GESIS - Leibniz Institute for the Social Sciences, the European Parliamentary Research Service, and several market and public opinion research institutes in Germany and Sweden. At GESIS, she is part of KODAQS, researching and educating…

🚨 Upcoming: "AIn't Nothing But a Survey? Using Large Language Models for Coding Open-Ended Survey Responses"

👤 Leah von der Heyde (GESIS)

🗓️ Wed, April 22, 13:45-15:15 CET

📺 Register for the live stream: us02web.zoom.us/meeting/regi...

🔗 socialsciencedatalab.mzes.uni-mannheim.de/page/events/

Infographic promoting registration for the Summer Institute in Survey Research Techniques with the main message to sharpen your survey research skills and that registration is open; text includes Institute for Social Research Summer Institute in Survey Research Techniques University of Michigan, headline Sharpen Your Survey Research Skills, bullets Taught by leading experts, Flexible online course options, Invest in your future, callouts Registration Open and Registration Link in Comments, and website si.isr.umich.edu, with an ISR logo and an illustration of a person in headphones attending an online class on a computer with three video call participants and charts on screen.

Registration is open for the Summer Institute in Survey Research Techniques at ISR!

Learn from leading experts, build flexible online coursework, and strengthen your survey research skills this summer. Register now and view the class catalog below.

We opened a new PhD position in our department focusing on CSS research on and with AI agents. Please share the job ad and contact us if you have questions: gesis.jobs.personio.de/job/2594220?...

Partisan nonresponse bias in a nutshell

GESIS Summer School Data Science Techniques for Survey Researchers 03 – 07 August 2026 | Cologne Anna Steinberg Schulten (LMU), Fiona Draxler (University of Mannheim)

Are you a survey researcher eager to learn data science?
In our #GESISsummerschool course, learn how to collect and analyze digital behavioral and traditional survey data using modern data science tools – and how to apply them effectively to real-world research questions.

➡️ t1p.de/GSS26-C4

How many times per week do you eat fast food or fried food? more than half nearly every day not at all several

Don’t randomize response options like this 💀

While we’re doing this, it’s pronounced “lick-ert”. Not “like-ert”.

A Study on Customer Support Team Configuration and Service Quality in Financial Services Enterprises A Study on Dispatcher Scheduling and Service On-Time Rate in Urban Public Transportation Systems A Study on the Impact of Member Mobility on Research Output in University Research Teams Authors Matthew R. Collins1, Daniel T. Harris2, James A. Wilson3* Affiliations Melbourne School of Engineering, The University of Melbourne, Parkville, VIC 3010, Australia Corresponding author: james.wilson@unimelb-placeholder.edu Abstract Customer support teams play a crucial role in ensuring service quality in financial services enterprises, and the rationality of their staffing directly affects customer experience. This study analyzes the relationship between staff size and service quality indicators, focusing on the configuration characteristics of customer support teams. Based on 18 consecutive months of operational data from the customer support center of a financial services enterprise, the sample includes 96 service teams, 2,430 customer service personnel, and over 3.2 million customer service records. Service quality is measured by average response time, first-time resolution rate, and customer satisfaction score. A generalized 1 configuration variables on service quality customer service team is controlled withi A Study on the Relationship between Labor Structure and Production Efficiency in Overseas Factories of Multinational Manufacturing Enterprises Authors Sebastian Weber1, Lukas Schneider2, Johannes Müller3* Affiliations Department of Civil, Geo and Environmental Engineering, Technical University of Munich (TUM), 80333 Munich, Germany *Corresponding author: johannes.mueller@tum-placeholder.edu Abstract Public transportation systems have high requirements for service on-time rate, and the rationality of dispatcher scheduling directly affects operational stability. This study analyzes the relationship between dispatcher scheduling and service on-time rate. The stud…

Someone went to the trouble of creating 5 fake OSF accounts today, linking to 5 fake ORCID accounts, and generating 5 fake papers to submit to SocArXiv, with fake author and emails. Dude, if you are reading this, I hope you get the help you need (or a better job).

🚀Introducing 𝐆𝐔𝐈𝐃𝐄-𝐋𝐋𝐌: A reporting checklist for using LLMs in behavioral & social science

✅GUIDE-LLM is a reporting checklist designed by 80+ experts to improve transparency, reproducibility & ethical accountability of LLM-based research

📄 llm-checklist.com

Interested in causal inference with survey data? Join the GESIS Summer School course with @tobiaswolbring.bsky.social and me:
training.gesis.org?site=pDetail...

@gesistraining.bsky.social

it set this one back when everyone was doing it
go.bsky.app/3H1Pf9z

Another day, another stupid Excel chart.

Data Visualization A Practical Introduction

Here’s a full draft of the upcoming second edition of my “Data Visualization: A Practical Introduction”: socviz.co

Screenshot of the "Does that use a lot of energy?" online app

Hannah Ritchie has built a fun little tool where you can compare energy usage of various products and activities.

This is super helpful imho, because it's so hard to develop intuitions even just about the scales involved here.

hannahritchie.substack.com/p/does-that-...

We are happy to have been part of the inspiring #GOR2026, where the KODAQS team presented research on data donations, satisficing, recruitment mechanisms, and awareness of data quality.

We are especially proud of Leah von der Heyde, who received the best dissertation award👏

Irena Kogan erhält Landesforschungspreis 2026 | Die Professorin für Soziologie und Gesellschaftsvergleich an der Universität Mannheim sowie ehemalige Direktorin des Mannheimer Zentrums für Europäische Sozialforschung (MZES) ist Preisträgerin des La...

I Kogan, Kollegin in der Fakultät für Sozialwissenschaften an der Uni Mannheim, erhält den Landes­forschungs­preises Baden-Württemberg 2026 für ihre Grundlagenforschung zu Bildungs- und Berufs­chancen von Migrant*innen.
Tolle Nachrichten und well-deserved!
www.uni-mannheim.de/news/irena-k...

#BlueShell #EarlyCareer #SpeedNetworking
#GOR26 – don’t miss the Early Career Speed Networking Event:
www.conftool.org/gor...

GESIS supports young scientists! Meet you in Blue Shell in Cologne!

❗📣 Great news:
Mannheim sociologist and former MZES director Irena Kogan has been awarded the 2026 research prize of the state of Baden-Württemberg for outstanding achievements in basic research.
Congratulations on this high Honour! 👏🥳🏆

Press release (in German):
www.uni-mannheim.de/newsroom/pre...

🎉 The KODAQS Data Quality Academy Individual Training is open for registration!

➡️Free and flexible online learning resource
➡️ Content selection based on interests and knowledge level
➡️ Learning paths for survey, digital behavioral, and linked data

👉 Regiser: www.gesis.org/en/gesis-tra...

📚 Special issue in Kölner Zeitschrift für Soziologie on Explanation and Causality in Sociology. Essential reading on where causal inference in sociology is heading
link.springer.com/collections/...

Ranking a strongly agree to strongly disagree scale is a new one for me…

We regret to inform you that your paper cannot be considered for publication, but we encourage you to submit it to our GOLD Open Access sister journal

Really enjoyed writing this piece with @heinzleitgoeb.bsky.social. Helped me structure my own thinking about when and how to use digital behavioral data for causal inference. Hope others find it useful as well!

Careers - BlueLabs We’re always looking to add new talent to our growing team of strategists, data scientists, and software engineers who operate at the forefront of data

Love surveys? We're hiring!

We're looking for new members of the polling team at @bluelabs.bsky.social. Two roles are focused on execution of day-to-day polling operations (Polling Manager, Lead Polling Manager) while the Survey Scientist is an R&D role!

Share & apply!
bluelabs.com/careers/

Causal Inferences from Digital Behavioral Data - KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie In recent years, digital behavioral data (DBD) have emerged as a powerful resource in social science research. Their ubiquity, granularity, complexity, and continuous collection provide new opportunit...

Joint paper with @floriankeusch.bsky.social out now: We discuss opportunities and challenges of causal inference from digital behavioral data, and methodological approaches for making these data fit for purpose:
link.springer.com/article/10.1...

Causal Machine Learning: A Deductive–Inductive Framework for Sociological Research - KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie Causal explanation is central to sociological research, shaping both theoretical development and empirical inquiry. This paper argues that causal machine learning—which integrates deductive identifica...

New paper on causal machine learning with Nanum Jeon @nanum-jeon.bsky.social link.springer.com/article/10.1...