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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.08940 |
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| _version_ | 1866915664527097856 |
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| author | Jani, Hemakshi Karia, Mitish Gohil, Meet Bhadja, Rahul Yacoub, Aznam Khan, Shafaq |
| author_facet | Jani, Hemakshi Karia, Mitish Gohil, Meet Bhadja, Rahul Yacoub, Aznam Khan, Shafaq |
| contents | This paper describes the development of Psychlysis, a work-in-progress questionnaire-based machine learning application analyzing the user's current state of mind and suggesting ways to improve their mood using Machine Learning. The application utilizes the OCEAN model to understand the user's personality traits and make customized suggestions to enhance their well-being. The proposed application focus on improving the user's mood rather than just detecting their emotions. Preliminary results of the model are presented, showing the potential of the application in predicting the user's mood and providing personalized recommendations. The paper concludes by highlighting the potential benefits of such an application for various societal segments, including doctors, individuals, and mental health organizations, in improving emotional well-being and reducing the negative impact of mental health issues on daily life. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_08940 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Psychlysis: Towards the Creation of a Questionnaire-based Machine Learning Tool to Analyze States of Mind Jani, Hemakshi Karia, Mitish Gohil, Meet Bhadja, Rahul Yacoub, Aznam Khan, Shafaq Human-Computer Interaction This paper describes the development of Psychlysis, a work-in-progress questionnaire-based machine learning application analyzing the user's current state of mind and suggesting ways to improve their mood using Machine Learning. The application utilizes the OCEAN model to understand the user's personality traits and make customized suggestions to enhance their well-being. The proposed application focus on improving the user's mood rather than just detecting their emotions. Preliminary results of the model are presented, showing the potential of the application in predicting the user's mood and providing personalized recommendations. The paper concludes by highlighting the potential benefits of such an application for various societal segments, including doctors, individuals, and mental health organizations, in improving emotional well-being and reducing the negative impact of mental health issues on daily life. |
| title | Psychlysis: Towards the Creation of a Questionnaire-based Machine Learning Tool to Analyze States of Mind |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2512.08940 |