activity
20232025
most citedAI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images

11 citations · 28 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2025

Beyond the Explicit: A Bilingual Dataset for Dehumanization Detection in Social Media

Dennis Assenmacher, Paloma Piot, Katarina Laken +2

Digital dehumanization, although a critical issue, remains largely overlooked within the field of computational linguistics and Natural Language Processing. The prevailing approach…

cs.CY2025

Learning from Convenience Samples: Fine-Tuning LLMs to Predict Voting Choices from Biased Survey Samples

Tobias Holtdirk, Dennis Assenmacher, Arnim Bleier +1

Survey research increasingly relies on convenience samples as rising costs and nonresponse make representative probability sampling more difficult. This creates a central challenge…

cs.CL2025

A Modular Taxonomy for Hate Speech Definitions and Its Impact on Zero-Shot LLM Classification Performance

Matteo Melis, Gabriella Lapesa, Dennis Assenmacher

Detecting harmful content is a crucial task in the landscape of NLP applications for Social Good, with hate speech being one of its most dangerous forms. But what do we mean by hat…

cs.CL2024★ 1 cited

Personas with Attitudes: Controlling LLMs for Diverse Data Annotation

Leon Fröhling, Gianluca Demartini, Dennis Assenmacher

We present a novel approach for enhancing diversity and control in data annotation tasks by personalizing large language models (LLMs). We investigate the impact of injecting diver…

cs.CL2024

Sexism Detection on a Data Diet

Rabiraj Bandyopadhyay, Dennis Assenmacher, Jose M. Alonso Moral +1

There is an increase in the proliferation of online hate commensurate with the rise in the usage of social media. In response, there is also a significant advancement in the creati…

cs.CL2024★ 8 cited

The Unseen Targets of Hate -- A Systematic Review of Hateful Communication Datasets

Zehui Yu, Indira Sen, Dennis Assenmacher +5

Machine learning (ML)-based content moderation tools are essential to keep online spaces free from hateful communication. Yet, ML tools can only be as capable as the quality of the…

cs.CR2024★ 11 cited

AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images

Jonas Ricker, Dennis Assenmacher, Thorsten Holz +2

Recent advances in the field of generative artificial intelligence (AI) have blurred the lines between authentic and machine-generated content, making it almost impossible for huma…

cs.CL2023

People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection

Indira Sen, Dennis Assenmacher, Mattia Samory +3

NLP models are used in a variety of critical social computing tasks, such as detecting sexist, racist, or otherwise hateful content. Therefore, it is imperative that these models a…

cs.SI2023

You are a Bot! -- Studying the Development of Bot Accusations on Twitter

Dennis Assenmacher, Leon Fröhling, Claudia Wagner

The characterization and detection of bots with their presumed ability to manipulate society on social media platforms have been subject to many research endeavors over the last de…

cs.SI2023★ 8 cited

Just Another Day on Twitter: A Complete 24 Hours of Twitter Data

Juergen Pfeffer, Daniel Matter, Kokil Jaidka +13

At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of int…