47 citations · 64 across the 9 of their papers we have counts for
10 papers
Large language models replicate and predict human cooperation across experiments in game theory
Andrea Cera Palatsi, Samuel Martin-Gutierrez, Ana S. Cardenal +1
Large language models (LLMs) are increasingly deployed as decision-making agents in high-stakes domains and as imitators of human behavior in the social and behavioral sciences. Ye…
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…
A Decade of News Forum Interactions: Threaded Conversations, Signed Votes, and Topical Tags
Emma Fraxanet, Vicenç Gómez, Andreas Kaltenbrunner +1
We present a large-scale, longitudinal dataset capturing user activity on the online platform of DerStandard, a major Austrian newspaper. The dataset spans ten years (2013-2022) an…
Dynamics of collective minds in online communities
Seungwoong Ha, Henrik Olsson, Kresimir Jaksic +2
Collective discourse and action are driven by collective minds. These shared semantic representations and related processes shape societal responses to critical societal challenges…
Only a Little to the Left: A Theory-grounded Measure of Political Bias in Large Language Models
Mats Faulborn, Indira Sen, Max Pellert +2
Prompt-based language models like GPT4 and LLaMa have been used for a wide variety of use cases such as simulating agents, searching for information, or for content analysis. For a…
Extracting Affect Aggregates from Longitudinal Social Media Data with Temporal Adapters for Large Language Models
Georg Ahnert, Max Pellert, David Garcia +1
This paper proposes temporally aligned Large Language Models (LLMs) as a tool for longitudinal analysis of social media data. We fine-tune Temporal Adapters for Llama 3 8B on full…
Unpacking polarization: Antagonism and Alignment in Signed Networks of Online Interaction
Emma Fraxanet, Max Pellert, Simon Schweighofer +2
Political conflict is an essential element of democratic systems, but can also threaten their existence if it becomes too intense. This happens particularly when most political iss…
Validating daily social media macroscopes of emotions
Max Pellert, Hannah Metzler, Michael Matzenberger +1
To study emotions at the macroscopic level, affective scientists have made extensive use of sentiment analysis on social media text. However, this approach can suffer from a series…
Social media emotion macroscopes reflect emotional experiences in society at large
David Garcia, Max Pellert, Jana Lasser +1
Social media generate data on human behaviour at large scales and over long periods of time, posing a complementary approach to traditional methods in the social sciences. Millions…
Dashboard of sentiment in Austrian social media during COVID-19
Max Pellert, Jana Lasser, Hannah Metzler +1
To track online emotional expressions of the Austrian population close to real-time during the COVID-19 pandemic, we build a self-updating monitor of emotion dynamics using digital…