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@article{198648,
        author = {N Ciri and K Nandini and M Eekshitha and N Venkata Subba Reddy},
        title = {AI Powered Mental Health Chatbot with Sentiment Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {10995-11001},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198648},
        abstract = {Mental disorders such as anxiety, depression, and stress are on the rise nowadays. Despite the growing prevalence of mental disorders, most individuals do not receive adequate treatment due to factors such as social stigma, affordability issues, and the unavailability of mental healthcare providers. Digital advancements have facilitated the creation of innovative AI technologies that can aid in supporting individuals’ mental wellbeing. For instance, one technology includes a conversational AI chatbot that can interact with individuals through conversations, offering emotional support. Conventional mental health interventions mostly entail counseling sessions with a therapist and calling helplines. While these interventions are beneficial, they may not be accessible to everyone. Although there are few apps and websites that exist, most of them have strict algorithms and fail to understand the emotional state of an individual. Thus, they lack the ability to provide customized answers, which renders them ineffective. The objective of this project is to design an intelligent and empathetic chat bot that individuals can access through an online platform anytime and anywhere. While the chat bot will make use of a previously existing algorithmic structure, it will incorporate realtime emotion detection, thus allowing it to respond to user input appropriately. It will be able to answer the questions asked by the user in helpful and empathetic manner, depending on his/her emotional state. The system will be designed using web-based applications that will allow it to be user-friendly, fast, and easily updatable.},
        keywords = {Recommender Systems, Personalization, Competitive Programming, Full-Stack Development, Node.js, React, Educational Technology (EdTech), Information Filtering, User Profiling, API Integration, Skill Acquisition.},
        month = {April},
        }