Papers by Joan Plepi
FACTOID: A New Dataset for Identifying Misinformation Spreaders and Political Bias (2022.lrec-1)
Copied to clipboard
| Challenge: | Proactively identifying misinformation spreaders is an important step towards mitigating the impact of fake news on our society. |
| Approach: | They propose a new reddit dataset for fake news spreader analysis, called FACTOID, which tracks political discussions on Reddit since the beginning of 2020. |
| Outcome: | The proposed dataset contains over 4K users with 3.4M posts and includes their credibility level (very low to very high) and political bias strength (extreme right to extreme left). |
Corpus Considerations for Annotator Modeling and Scaling (2024.naacl-long)
Copied to clipboard
| Challenge: | Recent trends in natural language processing and annotation tasks emphasize individual perspectives . annotator models that rely on a single ground truth may disregard valuable minority perspectives omissions . |
| Approach: | They propose a composite embedding approach to investigate annotator modeling techniques . they show that the commonly used user token model consistently outperforms more complex models . |
| Outcome: | The proposed model outperforms more complex models on a given dataset. |
Unifying Data Perspectivism and Personalization: An Application to Social Norms (2022.emnlp-main)
Copied to clipboard
| Challenge: | Obtaining a single ground truth is not possible or necessary for subjective tasks. |
| Approach: | They propose a set of personalization methods to model annotators and compare their effectiveness for predicting social norms. |
| Outcome: | The proposed model outperforms existing models and compares performance across subsets of social situations that vary by the closeness of the relationship between parties in conflict. |
Perspective Taking through Generating Responses to Conflict Situations (2024.findings-acl)
Copied to clipboard
| Challenge: | Language models struggle to understand and explain the beliefs of others, despite improving performance on a wide variety of tasks. |
| Approach: | They propose to modify the social-chem-101 corpus to allow for perspective-taking, the process of conceptualizing the point of view of another person. |
| Outcome: | The proposed models outperform the recent models conditioned on self-disclosures with high similarity to the conflict situation. |
Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networks (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing knowledge graphs are widely used for (complex) conversational question answering . LASAGNE improves the F1-score on eight out of ten question types . |
| Approach: | They propose a multi-task neural semantic parsing approach for (complex) conversational question answering over a knowledge graph using a transformer model and a Graph Attention Networks model. |
| Outcome: | The proposed approach outperforms baselines on eight out of ten question types on a standard dataset for complex sequential question answering. |
Perceived and Intended Sarcasm Detection with Graph Attention Networks (2021.findings-emnlp)
Copied to clipboard
| Challenge: | Existing sarcasm detection systems focus on exploiting linguistic markers, context, or user-level priors, but social studies suggest that the relationship between the author and the audience can be equally relevant for the sarkasmal usage and interpretation. |
| Approach: | They propose a framework leveraging a user context from their historical tweets together with social information from a users neighborhood in an interaction graph to contextualize the interpretation of the post. |
| Outcome: | The proposed framework combines a user context from their historical tweets with social information from a users neighborhood in an interaction graph to contextualize the interpretation of the post. |