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- Title
Transforming Arabic Text Analysis: Integrating Applied Linguistics with m-Polar Neutrosophic Set Mood Change and Depression on Social Media.
- Authors
Sivakumar, M.; Rabıyathul Basarıya, Abdul Rajak; Senthil, M.; Vetriselvi T.; Raja, G.; Rajavarman, R.
- Abstract
In this study, a new notion of m-polar neutrosophic set (MPNS) and m-polar neutrosophic topology is introduced. To achieve this goal, first, we explore numerous representations of the concept of MPNS and deliberate its definitive characteristics. Some operations on MPNS were established. A score function is proposed for comparing the MPN numbers (MPNNs). Next, an MPN topology is introduced and closure, frontier, interior, and exterior for MPNS are defined with representative examples. Depression is a popular mental health problem that disturbs a broad range of individuals worldwide. Generally, people who undergo from this attitude have problems like mood swings, low concentration, suicide, and dementia. A social media platform such as Twitter enables to interact and share videos and photos that express their moods. Hence, the studies on social media content present an overview of personal sentiments, such as depression. Research has been undertaken on depression recognition in English and less in Arabic. The recognition of depression from Arabic social media falls after owing to the lack of resources and techniques and the available difficulty of the Arabic language. This article presents a novel Applied Linguistics with m-Polar Neutrosophic Set Mood Change and Depression on Social Media (MPNS-MCDSM) technique on Arabic Text Analysis. To accomplish this, the MPNS-MCDSM method undertakes a data pre-processing stage to convert the input dataset into a beneficial format. In addition, the Glove word embedding method is applied to the feature extraction from the preprocessed dataset. For the classification process, the m-Polar Neutrosophic Set (MPNS) classifier can be applied. Finally, the Whale Optimization Algorithm (WOA) is applied for optimum adjustment of the hyperparameters related to the MPNS classifier. The simulation outcomes of the MPNS-MCDSM technique are verified on the benchmark dataset. The experimental result analysis of the MPNS-MCDSM technique shows its promising solution over other existing approaches.
- Subjects
NEUTROSOPHIC logic; MENTAL health; MENTAL depression; ALGORITHMS; ARABIC language
- Publication
International Journal of Neutrosophic Science (IJNS), 2025, Vol 25, Issue 2, p313
- ISSN
2692-6148
- Publication type
Academic Journal
- DOI
10.54216/IJNS.250227