aspg-25-2906-1792222768 20261017073928 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cognitive Human-Computer Interaction JCHCI 2771-1471 2771-1463 2024 8 2 Jayakaran P. Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College, India Litheeswaran S. Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College, India Janakiraman S. Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College, India Manikandan Undergraduate students, Department of Artificial Intelligence and Data Science, Panimalar Engineering College, India S. Malathi Department of Artificial Intelligence and Data Science, Panimalar Engineering College, India 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 25 29 2906 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCHCI.080206 https://americaspg.com/journal/25/article/2906 https://americaspg.com/storage/articles/manuscripts/01KWW8311X1GB9S434HNYWYRJP.pdf