Nahar, Abhinandan (2024) An Advanced Personalized Tweet Recommendation and Friend Suggestion System Using ChatGPT-3.5 Large Language Model, K-means Clustering, and Dynamic User Profiling. Masters thesis, Dublin, National College of Ireland.
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Abstract
As has been exhibited from this research paper, there is an imperative need to improve the tweet recommendations and friend suggestions in social media sites such as the ‘X’. The system uses some of the following advanced technologies such GPT-3. 5 for interest scoring, K-means clustering for organizing the content and cosine similarity for friend suggestions. It also uses dynamic user interest profiling which captures and evolves as the amount of interest changes and a new algorithm for recommendations. The paper also goes deep into the system specifications involving the technology architecture and the major algorithms. Performance findings reveal that the system successfully recommends the correct suggestions and friends. Thus, the existing challenges that are relevant to real-time processing of big data and the ethical issues remain unsolved, the study offers basic insights for further development of the recommendation systems of social media.
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