PsychWare

PsychWare is a sophisticated platform that utilizes a cutting-edge model to assess the mental well-being of Arabic students. The model employed in the project is designed specifically for detecting depression, and it leverages the power of NLP techniques. It has been trained on a vast amount of data, including a mixture of Arabic and English texts commonly found in online accounts of Arabic students. To handle the linguistic diversity and the mix of Arabic and English, the model incorporates preprocessing techniques. This includes removing diacritics, punctuations, repeating characters, and emojis from the text. By performing these preprocessing steps, the model ensures that the input text is clean and ready for analysis. The model itself is based on the transformer architecture, which has proven to be highly effective in NLP tasks. Transformers excel at understanding the semantic context and nuances of text, allowing PsychWare to accurately classify the emotional state of students, identify levels of exam anxiety, and detect potential signs of depression. Moreover, PsychWare recognizes the unique linguistic characteristics of the Arabic language, taking into account Arabic dialects and the presence of English words within the text. This enables the platform to provide a comprehensive analysis of Arabic students' mental well-being, transcending language barriers and delivering valuable insights to educators, parents, and mental health professionals. The integration of PHP and React in PsychWare ensures a seamless and user-friendly experience. The PHP backend handles the data processing and communication with the model, while the React frontend presents the results in an intuitive and visually appealing manner. PsychWare is poised to make a significant impact in the field of mental health assessment among Arabic students by harnessing the power of advanced NLP models and addressing the unique linguistic characteristics of Arabic and English texts.