Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Emotions are essential to any or all languages and are notoriously challenging to grasp. While numerous studies discussing the recognition of emotion in English, Arabic emotion reco remains in its early stages. The textual data with embedded emotions has increased considerably with the Internet and social networking platforms. This study aims to tackle the challenging problem of emotion detection in Arabic text. Recent studies found that dialect diversity and morpho Arabic language, with the limited access of annotated training datasets for Arabic emotions, pose the foremost significant challenges to Arabic emotion detection. Social media is kind of communication where users can share their thoughts and express emotions like joy, sadness, anger, surprise, hate, fear, so on some range of subjects in ways they’d not typically neutralize person. Social media also present different challenges which include spelling mistakes, new slang, and incorrect use of grammar. The previous few years have seen a giant increase in interest in text emotion detection The study of Arabic emotions might be a results of the Arab world’s conside politics and thus the economy. There are numerous uses for the automated recognition of emotions within the textual content on Facebook and Twitter, including company development, program design, content generation, and emergency response. in line with recent studies, it’s possible to identify emotions in English-language information.
Fatimah Khalil Aljwari. 2026. \u201cEmotion Detection in Arabic Text using Machine Learning Methods\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 23 (GJCST Volume 23 Issue G1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Emotions are essential to any or all languages and are notoriously challenging to grasp. While numerous studies discussing the recognition of emotion in English, Arabic emotion reco remains in its early stages. The textual data with embedded emotions has increased considerably with the Internet and social networking platforms. This study aims to tackle the challenging problem of emotion detection in Arabic text. Recent studies found that dialect diversity and morpho Arabic language, with the limited access of annotated training datasets for Arabic emotions, pose the foremost significant challenges to Arabic emotion detection. Social media is kind of communication where users can share their thoughts and express emotions like joy, sadness, anger, surprise, hate, fear, so on some range of subjects in ways they’d not typically neutralize person. Social media also present different challenges which include spelling mistakes, new slang, and incorrect use of grammar. The previous few years have seen a giant increase in interest in text emotion detection The study of Arabic emotions might be a results of the Arab world’s conside politics and thus the economy. There are numerous uses for the automated recognition of emotions within the textual content on Facebook and Twitter, including company development, program design, content generation, and emergency response. in line with recent studies, it’s possible to identify emotions in English-language information.
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