GESIS Training News

We care a lot about the health of our participants and lecturers. For this reason, all our events will be conducted as online training courses until the end of December 2021. This also applies to the GESIS Summer School in Survey Methodology and the GESIS Fall Seminar in Computational Social Science. As things stand at present, we are planning to continue our events program after this date with on-site courses. Should this not be possible, we will continue to offer digital formats as an alternative. More information here.

Take care of yourselves!

The workshop “Causality in the Social Sciences III – Heterogeneous Causal Effects” picks up on recent approaches and debates on treatment effect heterogeneity from three different angles: Interpretation of heterogeneous effects, estimating heterogeneous effects with observational and experimental data, and machine learning techniques for specification search. Confirmed keynote speakers are Jennie E. Brand (UCLA) and Richard Breen (Oxford University).

A maximum of 15 presentations by early career researchers – PhD students and PostDocs – will be accepted. Thanks for the support by the German Akademie für Soziologie and GESIS. Workshop participation (at GESIS Mannheim or online) is free of charge. Application deadline: 30 June 2021.

The GESIS Fall Seminar in Computational Social Science 2021 is held virtually from 13 September – 01 October 2021. It targets social scientists, researchers in the digital humanities, and practitioners from other disciplines who like to acquire technical skills and theoretical knowledge to collect and analyze digital behavioral data from the web, social media and digital text archives. Organized along two parallel tracks, it offers six one-week courses on computational social science methods and techniques using either R or Python. Courses will guide the participant through different stages of data collection (i.e., web scraping), data manipulation, data visualization, and data modeling (social network analysis, natural language processing, machine learning). Lectures in each course are complemented by hands-on exercises giving participants the opportunity to apply these methods to data. All courses are held in English.

Below, you can find an overview of this year's courses:

Computational Social Science with R

Introduction to Computational Social Science with Applications in R (13 - 17 September)

Dr. Aleksandra Urman (University of Bern / University of Zurich, Switzerland), Max Pellert (Medical University of Vienna / Technical University of Graz, Austria)

Automated Web Data Collection with R (20 - 24 September)

Dr. Theresa Gessler, Hauke Licht (University of Zurich, Switzerland)

Social Network Analysis with R (27 September - 01 October)

Dr. Silvia Fierăscu, Ianis Rușitoru (West University of Timișoara, Romania)   

Computational Social Science with Python

Introduction to Computational Social Science with Python (13 - 17 September)

Dr. Orsolya Vásárhelyi (University of Warwick, United Kingdom), Luis Natera (Central European University Budapest, Hungary)

Web Data Collection and Natural Language Processing in Python (20 - 24 September)

Indira Sen, Dr. Arnim Bleier, Julian Kohne, Dr. Fabian Flöck (GESIS, Germany)

A Practical Introduction to Machine Learning in Python (27 September - 01 October)

Assoc. Prof. Damian Trilling, Assist. Prof. Anne Kroon (University of Amsterdam, The Netherlands)           

Thanks to our cooperation with the a.r.t.e.s. Graduate School for the Humanities at the University of Cologne participants of the Fall Seminar may earn 2 European Credit Transfer System (ECTS) points per course for active participation.

For detailed course descriptions and registration, please visit our website and sign up (if courses are already fully booked, please sign in the waiting list) here.

Cornelia is a social scientist and head of the team Questionnaire Design & Evaluation at GESIS. She has been working as research associate in the GESIS pretesting unit since April, 2012. Together with the staff of the pretesting unit, she has conducted numerous cognitive pretests for various research projects and survey programs. Her research focuses on methods for testing and evaluating survey questionnaires and questionnaire design. Together with Dr. Timo Lenzner she will teach the course on “Pretesting Survey Questions” at the GESIS Summer School in August 2021.

How did you become interested in your subject?

I studied social sciences to learn more about how relationships are formed, and attitudes build. The survey is a cornerstone in the social science toolbox to gather information about people’s values and attitudes simply by asking questions. How different design decisions or question wordings can affect question comprehensibility and answering has fascinated me ever since. Questionnaire design and pretesting are of particular importance and interest as respondents’ answers to survey questions are used to measure public opinion and to inform political decisions.

What lessons can participants draw from your GESIS course?

One crucial step to accomplish that survey data are valid, reliable, and unbiased is that the questions are formulated in a way that respondents easily and consistently interpret them in the ways intended by the researchers. This is the task of survey pretesting. By the end of our course, participants will be familiar with current cognitive pretesting methods and know how to apply the various methods to evaluate their questionnaires.

What do you enjoy most about being a social scientist?

What I enjoy most about being a social scientist is that the knowledge can be so widely applied. The findings from survey methodology are relevant for many disciplines. I also enjoy learning new things and getting inspired every day by working and collaborating with many interesting people with different backgrounds. I am therefore very much looking forward to getting to know this year’s GESIS Summer School participants.

We thank Cornelia for her interesting insights and look forward to their class.