5 papers
Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation
Bolei Ma, Yong Cao, Indira Sen +4
Large Language Models (LLMs) are increasingly used to simulate public opinion and other social phenomena. Most current studies constrain these simulations to multiple-choice or sho…
Neural network embeddings recover value dimensions from psychometric survey items on par with human data
Max Pellert, Clemens M. Lechner, Indira Sen +1
We demonstrate that embeddings derived from large language models, when processed with "Survey and Questionnaire Item Embeddings Differentials" (SQuID), can recover the structure o…
Sensitive Content Classification in Social Media: A Holistic Resource and Evaluation
Dimosthenis Antypas, Indira Sen, Carla Perez-Almendros +2
The detection of sensitive content in large datasets is crucial for ensuring that shared and analysed data is free from harmful material. However, current moderation tools, such as…
Tell Me What You Know About Sexism: Expert-LLM Interaction Strategies and Co-Created Definitions for Zero-Shot Sexism Detection
Myrthe Reuver, Indira Sen, Matteo Melis +1
This paper investigates hybrid intelligence and collaboration between researchers of sexism and Large Language Models (LLMs), with a four-component pipeline. First, nine sexism res…
From Measurement Instruments to Data: Leveraging Theory-Driven Synthetic Training Data for Classifying Social Constructs
Lukas Birkenmaier, Matthias Roth, Indira Sen
Computational text classification is a challenging task, especially for multi-dimensional social constructs. Recently, there has been increasing discussion that synthetic training…