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@article{202839,
        author = {Yogita Sawant and Vaishnavi Pawar and Sejal khopade and Amruta vasav},
        title = {Region-Based YouTube Trend Analysis Using Thumbnails},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {7791-7798},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202839},
        abstract = {One of the most popular video-sharing sites is now YouTube, and in this case, thumbnails have a significant role in capturing the audience. Most of the creators come up with catchy thumbnails to boost the number of clicks but this is usually deceptive or exaggerated and there is a mismatch between the content and the expectations of the users. This lowers user confidence and has an impact on content transparency. In order to solve this problem, this paper suggests a Region-Aware YouTube Thumbnail AI Analyzer. The system is a web-based application, which analyses the thumbnails uploaded by users in real-time. It uses image processing, Optical Character Recognition (OCR) to extract text and emotion detection to identify exaggerated expressions. The system has a special feature of analysis by the region, which examines the thumbnails based on the content patterns by the regions. This enhances better detection accuracy and relevancy as opposed to the traditional methods. These findings indicate that the combination of several methods can be effective in detecting the misleading thumbnails. The system is easy to use and applicable in the real world. Altogether, this study contributes to better content reliability and allows understanding the authenticity of thumbnails better.},
        keywords = {YouTube Thumbnail Analysis, Clickbait Detection, Region-Aware System, Image Processing, Optical Character Recognition (OCR), Emotion Detection, Artificial Intelligence, Computer Vision, Streamlit Application, Real-Time Analysis},
        month = {May},
        }