7 citations · 7 across the 7 of their papers we have counts for
6 papers · 1 filter
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…
Deepfake tweets automatic detection
Adam Frej, Adrian Kaminski, Piotr Marciniak +3
This study addresses the critical challenge of detecting DeepFake tweets by leveraging advanced natural language processing (NLP) techniques to distinguish between genuine and AI-g…