What question did this study set out to answer?

The aim is to explore how large language models can enhance social science research workflows while considering data quality.

June 18, 2026Open Access

LLMs in the Research Workflow Slide deck

Key Points

The aim is to explore how large language models can enhance social science research workflows while considering data quality.
Introduction of different types of large language models and their functionalities.
Discussion of access options and effective prompting strategies for LLMs.
Examination of data quality impacts and proposed mitigation strategies for reproducibility.
Identified key functionalities of LLMs relevant to social science research.
Outlined practical strategies for improving data quality when using LLMs.
Provided recommendations for implementing robust reporting standards for enhanced reproducibility.

Abstract

In this presentation, large language models (LLMs) are introduced as a tool in the social science research workflow. LLMs can be used for a multitude of possible tasks, but in order to use them effectively, an understanding of how they work is needed - both from a technical and data quality perspective. The presentation introduces the internal logic of LLMs and what they can be used for, as well as different types of LLMs, access options, and prompting strategies. Additionally, it discusses how these decisions impact data quality and explores mitigation strategies and reporting standards for better reproducibility. Presentation available after free registration: https://elearning.gesis.org/course/section.php?id=2574

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