CS3 Lab for Computational Survey and Social Science

Start of the project: 2023-Dec-01

CS3 lab for Computational Survey and Social Science is an interdisciplinary group of researchers from various fields assembling expert knowledge in survey methodology, ux research, machine learning, NLP, and generative AI. CS3 lab is led by Prof. Dr. Jan Karem Höhne and situated in the Research Infrastructure and Methods Department at the German Centre for Higher Education Research and Science Studies (DZHW). Together, the members of CS3 lab constantly explore new avenues for extending the methodological and analytical toolkit for substantive social science research.
We utilize online surveys as a comprehensive tool for collecting various digital data about people's attitudes, traits, and behaviors. This includes trace data from mobile apps, search queries, and website visits to, for example, draw conclusions about people’s living conditions. This is accompanied by research on smartphone sensors, such as accelerometer data for inferring motion conditions and activity levels. Similarly, we introduce qualitative research impulses to quantitative data collection. We started to work on fusing conversational AI-based interviewers with online surveys and gather voice answers to open narrative questions that are recorded through the built-in microphone of smartphones. In doing so, we are going beyond pure text-as-data methods extracting tonal cues to infer emotional and affective states in situ. Finally, we successively engage in social media sampling strategies evaluating data integrity. This especially includes the threat through bots that potentially shift research outcomes.
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Publications

Examining final comment questions with requests for written and oral answers.

Höhne, J. K., & Claaßen, J. (2024).
Examining final comment questions with requests for written and oral answers. International Journal of Market Research (online first). https://doi.org/10.1177/14707853241229329
Presentations

Inferring respondents’ emotional states from text and voice answers to open questions in a smartphone survey.

Claaßen, J., Höhne, J. K., Kern, C., & Avetisyan, H. (2024, März).
Inferring respondents’ emotional states from text and voice answers to open questions in a smartphone survey. Vortrag im Rahmen des WEB DATA OPP Workshops, Barcelona, Spain.

Respondent-centered incentives: Increasing answer provision when it comes to voice answers to open questions.

Höhne, J. K., Revilla, M., & Couper, M. P. (2024, März).
Respondent-centered incentives: Increasing answer provision when it comes to voice answers to open questions. Vortrag im Rahmen des WEB DATA OPP Workshops, Barcelona, Spain.

Inferring respondents’ emotional states from transcribed voice answers to open questions in a smartphone survey.

Claaßen, J., Höhne, J. K., Kern, C., & Avetisyan, H. (2024, März).
Inferring respondents’ emotional states from transcribed voice answers to open questions in a smartphone survey. Vortrag im Rahmen des Mobile Apps and Sensors in Surveys (MASS) Workshop, Washington, D.C., USA.

Exploring effects of life-like virtual interviewers on respondents’ answers in a smartphone survey.

Höhne, J. K., Conrad, F., Neuert, C., & Claaßen, J. (2024, Februar).
Exploring effects of life-like virtual interviewers on respondents’ answers in a smartphone survey. Vortrag im Rahmen der General Online Research (GOR) Conference, Köln.

API vs. human coder: Comparing the performance of speech-to-text transcription using voice answers from a smartphone survey.

Höhne, J. K., & Lenzner, T. (2024, Februar).
API vs. human coder: Comparing the performance of speech-to-text transcription using voice answers from a smartphone survey. Vortrag im Rahmen der General Online Research (GOR) Conference, Köln.

Head

Jan Karem Höhne
Prof. Dr. Jan Karem Höhne +49 511 450670-458

Members and collaborators

Website

https://jkhoehne.eu/cs3-lab/