Summary of Exu: Ai Models For Examining Multilingual Disinformation Narratives and Understanding Their Spread, by Jake Vasilakes et al.
ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread
by Jake Vasilakes, Zhixue Zhao, Ivan Vykopal, Michal Gregor, Martin Hyben, Carolina Scarton
First submitted to arxiv on: 30 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes the ExU project, which aims to develop AI-based models for multilingual disinformation analysis. The project focuses on two tasks: rumour stance classification and claim retrieval. To achieve this goal, the researchers conducted a user requirements survey to design tools that support fact-checking. The study suggests that machine learning models can be trained to classify rumours and retrieve claims across different languages, providing valuable insights for fact-checkers and journalists. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The ExU project is important because it helps address online disinformation by analyzing narratives in multiple languages. This allows fact-checkers and journalists to make informed decisions when dealing with large amounts of data. The study also highlights the importance of designing tools that support fact-checking, which can help improve the accuracy of information dissemination. |
Keywords
» Artificial intelligence » Classification » Machine learning
