collaborators

5 papers

cs.CL2025

Can Large Language Models Detect Verbal Indicators of Romantic Attraction?

Sandra C. Matz, Heinrich Peters, Moran Cerf +4

As artificial intelligence (AI) models become an integral part of everyday life, our interactions with them shift from purely functional exchanges to more relational experiences. F…

cs.HC2024

Social Media Use is Predictable from App Sequences: Using LSTM and Transformer Neural Networks to Model Habitual Behavior

Heinrich Peters, Joseph B. Bayer, Sandra C. Matz +3

The present paper introduces a novel approach to studying social media habits through predictive modeling of sequential smartphone user behaviors. While much of the literature on m…

cs.LG2024

Context-Aware Prediction of User Engagement on Online Social Platforms

Heinrich Peters, Yozen Liu, Francesco Barbieri +3

The success of online social platforms hinges on their ability to predict and understand user behavior at scale. Here, we present data suggesting that context-aware modeling approa…

cs.CL2024

Large Language Models Can Infer Psychological Dispositions of Social Media Users

Heinrich Peters, Sandra Matz

Large Language Models (LLMs) demonstrate increasingly human-like abilities across a wide variety of tasks. In this paper, we investigate whether LLMs like ChatGPT can accurately in…

cs.HC2024

Large Language Models Can Infer Personality from Free-Form User Interactions

Heinrich Peters, Moran Cerf, Sandra C. Matz

This study investigates the capacity of Large Language Models (LLMs) to infer the Big Five personality traits from free-form user interactions. The results demonstrate that a chatb…