dc.contributor.author | Bendebane, Lamia | |
dc.contributor.author | Bendebane, Lamia | |
dc.date.accessioned | 2025-03-17T09:49:51Z | |
dc.date.available | 2025-03-17T09:49:51Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | http://depot.umc.edu.dz/handle/123456789/14525 | |
dc.description.abstract | The World Health Organization (WHO) and various researchers have recently highlighted the global rise in mental disorders, emphasizing the serious implications for individuals’ mental health. This study focuses on predicting depression and anxiety disorders using textual data from social media | fr_FR |
dc.title | The Optimal Dataset Size Related to Epochs Number to Predict Depression and Anxiety from the Twitter Datase | fr_FR |
dc.type | Article | fr_FR |