Papers by Binny Mathew
HateCheckHIn: Evaluating Hindi Hate Speech Detection Models (2022.lrec-1)
Copied to clipboard
| Challenge: | Hate speech detection models are evaluated on a held-out test data, but they are incapable of identifying weaknesses. |
| Approach: | They propose to use multilingual hate speech detection models to evaluate their performance on social media conversation. |
| Outcome: | The proposed model can detect hate speech in multiple languages using a real-world conversation on social media. |
InfFeed: Influence Functions as a Feedback to Improve the Performance of Subjective Tasks (2024.lrec-main)
Copied to clipboard
| Challenge: | InfFeed uses influence functions to compute the influential instances for a target instance. |
| Approach: | They propose an apparatus that uses influence functions to compute the influential instances for a target instance. |
| Outcome: | The proposed model outperforms the state-of-the-art baselines by 4% for hate speech classification, 3.5% for stance classification, and 3% for irony and 2% for sarcasm detection. |
A Community-Centric Perspective for Characterizing and Detecting Anti-Asian Violence-Provoking Speech (2024.acl-long)
Copied to clipboard
Gaurav Verma, Rynaa Grover, Jiawei Zhou, Binny Mathew, Jordan Kraemer, Munmun Choudhury, Srijan Kumar
| Challenge: | Using data from 420k Twitter posts, we characterize anti-Asian violence-provoking speech and collect a community-crowdsourced dataset to facilitate its large-scale detection. |
| Approach: | They develop a codebook to characterize anti-Asian violence-provoking speech and collect a community-crowdsourced dataset to facilitate its large-scale detection. |
| Outcome: | The proposed codebook analyzes 420k tweets over 3 years and compares classifiers with hateful speech classifier classifier to detect hateful content. |