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@article{175598,
        author = {Ms. P .Jeyakani and S Krithik Aditya and S Shyam Ganesh and A Somesh Varman},
        title = {ENHANCED DEPRESSION DETECTION ON SOCIAL MEDIA USING AI WITH CUSTOM VISUALIZATIONS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {3722-3727},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175598},
        abstract = {This study focuses on leveraging deep learning techniques to detect early signs of depression in social media visuals and captions. The system analyzes both visual content and textual data, such as Instagram posts and captions, to identify subtle emotional cues indicative of depression. By integrating natural language processing for textual analysis and emotion detection models for visuals, the project provides a holistic understanding of a user's mental health. The aim is to develop a prototype capable of automatic depression detection, offering a valuable tool for mental health professionals and organizations to monitor public health trends and support timely intervention. This research highlights the transformative potential of AI in advancing mental health care and awareness.},
        keywords = {Depression Detection, Deep Learning, Social Media Analysis, Sentiment Analysis, Emotional Recognition.},
        month = {April},
        }