Fact Check-Worthiness Detection with Contrastive Ranking
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Check-worthiness detection aims at predicting which sentences should be prioritized for fact-checking. A typical use is to rank sentences in political debates and speeches according to their degree of check-worthiness. We present the first direct optimization of sentence ranking for check-worthiness; in contrast, all previous work has solely used standard classification based loss functions. We present a recurrent neural network model that learns a sentence encoding, from which a check-worthiness score is predicted. The model is trained by jointly optimizing a binary cross entropy loss, as well as a ranking based pairwise hinge loss. We obtain sentence pairs for training through contrastive sampling, where for each sentence we find the top most semantically similar sentences with opposite label. Through a comparison to existing state-of-the-art check-worthiness methods, we find that our approach improves the MAP score by 11%.
Original language | English |
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Title of host publication | Experimental IR Meets Multilinguality, Multimodality, and Interaction - 11th International Conference of the CLEF Association, CLEF 2020, Proceedings |
Editors | Avi Arampatzis, Evangelos Kanoulas, Theodora Tsikrika, Stefanos Vrochidis, Hideo Joho, Christina Lioma, Carsten Eickhoff, Aurélie Névéol, Aurélie Névéol, Linda Cappellato, Nicola Ferro |
Publisher | Springer |
Publication date | 2020 |
Pages | 124-130 |
ISBN (Print) | 9783030582180 |
DOIs | |
Publication status | Published - 2020 |
Event | 11th Conference and Labs of the Evaluation Forum, CLEF 2020 - Thessaloniki, Greece Duration: 22 Sep 2020 → 25 Sep 2020 |
Conference
Conference | 11th Conference and Labs of the Evaluation Forum, CLEF 2020 |
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Land | Greece |
By | Thessaloniki |
Periode | 22/09/2020 → 25/09/2020 |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12260 LNCS |
ISSN | 0302-9743 |
- Check-worthiness, Contrastive ranking, Neural networks
Research areas
ID: 250486804