Papers by Flavio Toxvaerd
Will-They-Won’t-They: A Very Large Dataset for Stance Detection on Twitter (2020.acl-main)
Copied to clipboard
Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, Chryssi Giannitsarou, Flavio Toxvaerd, Nigel Collier
| Challenge: | stance detection is a key component of fake news detection, fact-checking and rumor verification. |
| Approach: | They propose to use a large dataset of English tweets for stance detection for a rumor verification task. |
| Outcome: | The proposed dataset contains 51,284 tweets in English, making it the largest available dataset of the type. |
STANDER: An Expert-Annotated Dataset for News Stance Detection and Evidence Retrieval (2020.findings-emnlp)
Copied to clipboard
Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, Chryssi Giannitsarou, Flavio Toxvaerd, Nigel Collier
| Challenge: | a new news dataset targets both stance detection (SD) and fine-grained evidence retrieval (ER) . stance Detection (SD), which is a form of multitask learning, has gained increasing interest in recent work . |
| Approach: | They propose a news dataset that targets both stance detection (SD) and fine-grained evidence retrieval (ER) their dataset is an expert-annotated news dataset with 3,291 articles. |
| Outcome: | The proposed dataset is a high-quality benchmark for future research in stance detection and evidence retrieval. |
Incorporating Stock Market Signals for Twitter Stance Detection (2022.acl-long)
Copied to clipboard
Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, Chryssi Giannitsarou, Flavio Toxvaerd, Nigel Collier
| Challenge: | stance detection is the task of automatically classifying the writer's opinion expressed in a text towards a particular target. |
| Approach: | They propose a robust multi-task neural architecture that combines textual input with high-frequency intra-day time series from stock market prices. |
| Outcome: | The proposed system achieves state-of-the-art on the wt–wt dataset. |