Journal of Cognitive Human-Computer Interaction JCHCI 2771-1463 2771-1471 10.54216/JCHCI https://www.americaspg.com/journals/show/2906 2021 2021 Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College. admin admin Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College. Litheeswaran. S. Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College. Janakiraman. S. Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College. Manikandan Manikandan Department of Artificial Intelligence and Data Science, Panimalar Engineering College. S. Malathi This research develops a novel approach for mood-based YouTube video suggestions. Using cutting-edge textual data analysis techniques, through the application of Natural Language Processing (NLP) techniques combined with sentiment analysis based on the FrameNet framework, users' everyday experiences and feelings are carefully analyzed to determine their current mood in the text. The process of content curation is made easier by the extraction of pertinent video metadata with the help of the YouTube API key. The integration of video metadata with textual mood extraction allows for the development of an extremely engaging and personalized content recommendation system. Users are provided with content that resonates with their current emotional state by matching the recommended movies' mood with the one deduced from the textual input. This improves user satisfaction and enriches their experience.   2024 2024 55 62 10.54216/JCHCI.080206 https://www.americaspg.com/articleinfo/25/show/2906