6 citations · 10 across the 11 of their papers we have counts for
6 papers · 1 filter
LLM-Generated Ads: From Personalization Parity to Persuasion Superiority
Elyas Meguellati, Stefano Civelli, Lei Han +3
As large language models (LLMs) become increasingly capable of generating persuasive content, understanding their effectiveness across different advertising strategies becomes crit…
Political Advertising on Facebook During the 2022 Australian Federal Election: A Social Identity Perspective
Stefano Civelli, Pietro Bernardelle, Frank Mols +1
The spread of targeted advertising on social media platforms has revolutionized political marketing strategies. Monitoring these digital campaigns is essential for maintaining tran…
Ideology-Based LLMs for Content Moderation
Stefano Civelli, Pietro Bernardelle, Nardiena A. Pratama +1
Large language models (LLMs) are increasingly used in content moderation systems, where ensuring fairness and neutrality is essential. In this study, we examine how persona adoptio…
Political Ideology Shifts in Large Language Models
Pietro Bernardelle, Stefano Civelli, Leon Fröhling +3
Large language models (LLMs) are increasingly deployed in politically sensitive contexts, raising concerns about their susceptibility to ideological biases. In this work, we examin…
Towards Detecting Persuasion on Social Media: From Model Development to Insights on Persuasion Strategies
Elyas Meguellati, Stefano Civelli, Pietro Bernardelle +3
Political advertising plays a pivotal role in shaping public opinion and influencing electoral outcomes, often through subtle persuasive techniques embedded in broader propaganda s…
The Impact of Persona-based Political Perspectives on Hateful Content Detection
Stefano Civelli, Pietro Bernardelle, Gianluca Demartini
While pretraining language models with politically diverse content has been shown to improve downstream task fairness, such approaches require significant computational resources o…