ANALYSIS OF YOUTUBE CONTENT SELECTION ALGORITHM WITH BIG DATA AND NATURAL LANGUAGE PROCESSING APPROACH

• Main Author: Febrianto Yohanes, Gilbert
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/79107
• Institution: Institut Teknologi Bandung

This research aims to develop a big data analysis system that utilizes Natural Language Processing (NLP) to categorize videos based on specific keyword themes on the YouTube platform. The research involves using an NLP tool, namely the Natural Language Toolkit (NLTK) in the Python programming language, to analyze text or transcripts related to these videos. In the context of this study, the videos under analysis are those from the YouTube platform covering various topics. The NLP method will be employed to identify keywords, topics, or content associated with these videos. The outcome of this analysis will be used to categorize videos based on specific keyword themes, such as 'Japan,' for example. The anticipated results of this research aim to provide deeper insights into the use of NLP in big data analysis, particularly within the context of recommending video content based on keyword themes and predicting YouTube algorithms. The developed system holds the potential to enhance the relevance and personalization of video recommendations, which could be beneficial for videosharing platforms and end-users. This study supports advancements in big data analysis and NLP applications across various domains, including digital content management and a better understanding of user preferences.