1 code implementation • RANLP 2019 • Yoan Dinkov, Ivan Koychev, Preslav Nakov
Online media aim for reaching ever bigger audience and for attracting ever longer attention span.
1 code implementation • 20 Oct 2019 • Yoan Dinkov, Ahmed Ali, Ivan Koychev, Preslav Nakov
Our analysis shows that the use of acoustic signal helped to improve bias detection by more than 6% absolute over using text and metadata only.
1 code implementation • ACL 2020 • Ramy Baly, Georgi Karadzhov, Jisun An, Haewoon Kwak, Yoan Dinkov, Ahmed Ali, James Glass, Preslav Nakov
Alternatively, we can profile entire news outlets and look for those that are likely to publish fake or biased content.
2 code implementations • EMNLP 2020 • Momchil Hardalov, Todor Mihaylov, Dimitrina Zlatkova, Yoan Dinkov, Ivan Koychev, Preslav Nakov
We perform various experiments with existing top-performing multilingual pre-trained models and we show that EXAMS offers multiple challenges that require multilingual knowledge and reasoning in multiple domains.
no code implementations • 27 Feb 2021 • Arnav Arora, Preslav Nakov, Momchil Hardalov, Sheikh Muhammad Sarwar, Vibha Nayak, Yoan Dinkov, Dimitrina Zlatkova, Kyle Dent, Ameya Bhatawdekar, Guillaume Bouchard, Isabelle Augenstein
The proliferation of harmful content on online platforms is a major societal problem, which comes in many different forms including hate speech, offensive language, bullying and harassment, misinformation, spam, violence, graphic content, sexual abuse, self harm, and many other.
no code implementations • 31 Mar 2021 • Sheikh Muhammad Sarwar, Dimitrina Zlatkova, Momchil Hardalov, Yoan Dinkov, Isabelle Augenstein, Preslav Nakov
The framework is based on a nearest-neighbour architecture.
no code implementations • RANLP 2021 • Krasimira Bozhanova, Yoan Dinkov, Ivan Koychev, Maria Castaldo, Tommaso Venturini, Preslav Nakov
We propose a novel framework for predicting the factuality of reporting of news media outlets by studying the user attention cycles in their YouTube channels.