7 papers
ClickGuard: Detecting and Spoiling Clickbait News with Informativeness Measures and Large Language Models
Wojciech Michaluk, Tymoteusz Urban, Mateusz Kubita +2
This paper presents an AI-driven browser extension that identifies clickbait to help users avoid misleading Internet articles. Moving beyond traditional detection, the application…
Clickbait detection: quick inference with maximum impact
Soveatin Kuntur, Panggih Kusuma Ningrum, Anna Wróblewska +2
We propose a lightweight hybrid approach to clickbait detection that combines OpenAI semantic embeddings with six compact heuristic features capturing stylistic and informational c…
Graph Neural Networks for Misinformation Detection: Performance-Efficiency Trade-offs
Soveatin Kuntur, Maciej Krzywda, Anna Wróblewska +4
The rapid spread of online misinformation has led to increasingly complex detection models, including large language models and hybrid architectures. However, their computational c…
Rewrite the News: Tracing Editorial Reuse Across News Agencies
Soveatin Kuntur, Nina Smirnova, Anna Wroblewska +2
This paper investigates sentence-level text reuse in multilingual journalism, analyzing where reused content occurs within articles. We present a weakly supervised method for detec…
Click it or Leave it: Detecting and Spoiling Clickbait with Informativeness Measures and Large Language Models
Wojciech Michaluk, Tymoteusz Urban, Mateusz Kubita +2
Clickbait headlines degrade the quality of online information and undermine user trust. We present a hybrid approach to clickbait detection that combines transformer-based text emb…
Fake News Detection: It's All in the Data!
Soveatin Kuntur, Anna Wróblewska, Marcin Paprzycki +1
This comprehensive survey serves as an indispensable resource for researchers embarking on the journey of fake news detection. By highlighting the pivotal role of dataset quality a…