A study on cross-lingual fake news detection in English and Arabic
| dc.contributor.advisor | Hakak, Saqib | |
| dc.contributor.author | Elba, Abdelrahman | |
| dc.date.accessioned | 2024-06-11T14:36:55Z | |
| dc.date.available | 2024-06-11T14:36:55Z | |
| dc.date.issued | 2024-04 | |
| dc.description.abstract | As fake news spreads across languages, the challenge of detecting it in linguistically diverse environments becomes increasingly critical. Existing fake news detection methods are predominantly monolingual and heavily biased towards resource-rich languages. Fake news detection models often encounter difficulties with language-specific limitations and fail to account for linguistic and cultural variations in cross-lingual scenarios. This research contributes a comprehensive cross-language analysis, exploring the effectiveness of various detection models in both monolingual and cross-lingual contexts. This thesis emphasizes the importance of translation models and their role in enhancing detection accuracy. The attention-based model proposed significantly enhances the effectiveness of fake news detection. The comprehensive cross-language analysis demonstrates the model’s superiority over existing methods, it showcases a significant improvement in detection accuracy, with a 15% increase over conventional methods. The results show an improvement in accuracy, indicating a promising direction for future research. | |
| dc.description.copyright | © Abdelrahman Elba, 2024 | |
| dc.format.extent | xii, 57 | |
| dc.format.medium | electronic | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/37980 | |
| dc.language.iso | en | |
| dc.publisher | University of New Brunswick | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Computer Science | |
| dc.title | A study on cross-lingual fake news detection in English and Arabic | |
| dc.type | master thesis | |
| oaire.license.condition | other | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | University of New Brunswick | |
| thesis.degree.level | masters | |
| thesis.degree.name | M.C.S. |