| What was written vs. who read it: News media profiling using text analysis and social media context R Baly, G Karadzhov, J An, H Kwak, Y Dinkov, A Ali, J Glass, P Nakov arXiv preprint arXiv:2005.04518, 2020 | 38 | 2020 |
| Predicting the leading political ideology of YouTube channels using acoustic, textual, and metadata information Y Dinkov, A Ali, I Koychev, P Nakov arXiv preprint arXiv:1910.08948, 2019 | 34 | 2019 |
| Detecting abusive language on online platforms: A critical analysis P Nakov, V Nayak, K Dent, A Bhatawdekar, SM Sarwar, M Hardalov, ... arXiv e-prints, arXiv: 2103.00153, 2021 | 27 | 2021 |
| EXAMS: A multi-subject high school examinations dataset for cross-lingual and multilingual question answering M Hardalov, T Mihaylov, D Zlatkova, Y Dinkov, I Koychev, P Nakov arXiv preprint arXiv:2011.03080, 2020 | 24 | 2020 |
| Detecting harmful content on online platforms: what platforms need vs. where research efforts go A Arora, P Nakov, M Hardalov, SM Sarwar, V Nayak, Y Dinkov, D Zlatkova, ... ACM Computing Surveys 56 (3), 1-17, 2023 | 17 | 2023 |
| Detecting toxicity in news articles: Application to Bulgarian Y Dinkov, I Koychev, P Nakov arXiv preprint arXiv:1908.09785, 2019 | 12 | 2019 |
| A neighborhood framework for resource-lean content flagging SM Sarwar, D Zlatkova, M Hardalov, Y Dinkov, I Augenstein, P Nakov Transactions of the Association for Computational Linguistics 10, 484-502, 2022 | 11 | 2022 |
| Predicting the factuality of reporting of news media using observations about user attention in their YouTube channels K Bozhanova, Y Dinkov, I Koychev, M Castaldo, T Venturini, P Nakov arXiv preprint arXiv:2108.12519, 2021 | 5 | 2021 |
