47 citations · 80 across the 5 of their papers we have counts for
7 papers
The Collective Turing Test: Large Language Models Can Generate Realistic Multi-User Discussions
Azza Bouleimen, Giordano De Marzo, Taehee Kim +5
Large Language Models (LLMs) offer new avenues to simulate online communities and social media. Potential applications range from testing the design of content recommendation algor…
AI could create a perfect storm of climate misinformation
Victor Galaz, Hannah Metzler, Stefan Daume +3
We are in the midst of a transformation of the digital news ecosystem. The expansion of online social networks, the influence of recommender systems, increased automation, and new…
LEIA: Linguistic Embeddings for the Identification of Affect
Segun Taofeek Aroyehun, Lukas Malik, Hannah Metzler +3
The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of…
Detecting potentially harmful and protective suicide-related content on twitter: A machine learning approach
Hannah Metzler, Hubert Baginski, Thomas Niederkrotenthaler +1
Research shows that exposure to suicide-related news media content is associated with suicide rates, with some content characteristics likely having harmful and others potentially…
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…