Exploring the Role of Emotions in Arabic Rumor Detection in Social Media
With the increasing reliance on social media as a primary source of news, the proliferation of rumors has become a pressing global concern that negatively impacts various domains, including politics, economics, and societal well-being. While significant efforts have been made to identify and debunk...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/15/8815 |
| _version_ | 1797587116842024960 |
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| author | Hissa F. Al-Saif Hmood Z. Al-Dossari |
| author_facet | Hissa F. Al-Saif Hmood Z. Al-Dossari |
| author_sort | Hissa F. Al-Saif |
| collection | DOAJ |
| description | With the increasing reliance on social media as a primary source of news, the proliferation of rumors has become a pressing global concern that negatively impacts various domains, including politics, economics, and societal well-being. While significant efforts have been made to identify and debunk rumors in social media, progress in detecting and addressing such issues in the Arabic language has been limited compared to other languages, particularly English. This study introduces a context-aware approach to rumor detection in Arabic social media, leveraging recent advancements in Natural Language Processing (NLP). Our proposed method evaluates Arabic news posts by analyzing the emotions evoked by news content and recipients towards the news. Moreover, this research explores the impact of incorporating user and content features into emotion-based rumor detection models. To facilitate this investigation, we present a novel Arabic rumor dataset, comprising both news posts and associated comments, which represents a first-of-its-kind resource in the Arabic language. The findings from this study offer promising insights into the role of emotions in rumor detection and may serve as a catalyst for further research in this area, ultimately contributing to improved detection and the mitigation of misinformation in the digital landscape. |
| first_indexed | 2024-03-11T00:31:45Z |
| format | Article |
| id | doaj.art-d87e491247ab4dc5bd4c79909aa4cc7d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T00:31:45Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d87e491247ab4dc5bd4c79909aa4cc7d2023-11-18T22:37:56ZengMDPI AGApplied Sciences2076-34172023-07-011315881510.3390/app13158815Exploring the Role of Emotions in Arabic Rumor Detection in Social MediaHissa F. Al-Saif0Hmood Z. Al-Dossari1Computer Science and Information Systems, University of King Saud, Riyadh 11421, Saudi ArabiaComputer Science and Information Systems, University of King Saud, Riyadh 11421, Saudi ArabiaWith the increasing reliance on social media as a primary source of news, the proliferation of rumors has become a pressing global concern that negatively impacts various domains, including politics, economics, and societal well-being. While significant efforts have been made to identify and debunk rumors in social media, progress in detecting and addressing such issues in the Arabic language has been limited compared to other languages, particularly English. This study introduces a context-aware approach to rumor detection in Arabic social media, leveraging recent advancements in Natural Language Processing (NLP). Our proposed method evaluates Arabic news posts by analyzing the emotions evoked by news content and recipients towards the news. Moreover, this research explores the impact of incorporating user and content features into emotion-based rumor detection models. To facilitate this investigation, we present a novel Arabic rumor dataset, comprising both news posts and associated comments, which represents a first-of-its-kind resource in the Arabic language. The findings from this study offer promising insights into the role of emotions in rumor detection and may serve as a catalyst for further research in this area, ultimately contributing to improved detection and the mitigation of misinformation in the digital landscape.https://www.mdpi.com/2076-3417/13/15/8815social mediarumor detectionsentimentsemotions analysisuser-credibilityArabic NLP |
| spellingShingle | Hissa F. Al-Saif Hmood Z. Al-Dossari Exploring the Role of Emotions in Arabic Rumor Detection in Social Media Applied Sciences social media rumor detection sentiments emotions analysis user-credibility Arabic NLP |
| title | Exploring the Role of Emotions in Arabic Rumor Detection in Social Media |
| title_full | Exploring the Role of Emotions in Arabic Rumor Detection in Social Media |
| title_fullStr | Exploring the Role of Emotions in Arabic Rumor Detection in Social Media |
| title_full_unstemmed | Exploring the Role of Emotions in Arabic Rumor Detection in Social Media |
| title_short | Exploring the Role of Emotions in Arabic Rumor Detection in Social Media |
| title_sort | exploring the role of emotions in arabic rumor detection in social media |
| topic | social media rumor detection sentiments emotions analysis user-credibility Arabic NLP |
| url | https://www.mdpi.com/2076-3417/13/15/8815 |
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