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Analysis of Comments on Youtube Videos using Hadoop


Scalable and Secure Big Data I

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Abstract


YouTube is a popular video sharing portal of today's time which also allows users to provide their feedback in form of comments, likes and subscriptions. Analysis of this feedback plays a crucial role in enhancement of video content to suit the need of the time. The comments, in specific, can highly benefit a new user in forming an informed and decisive opinion about a particular video. The work presents a system to perform a detailed analysis and classification of the comments on YouTube videos. The comments corresponding to videos have been ingested into the Hadoop Distributed File System (HDFS) and queried with the Hadoop analytical software, Hive. Further, sentiment analysis of these comments has been performed using Python. The proposed system has been evaluated by executing multiple self-designed queries on the YouTube data. Results of execution times of these queries have been tabulated and presented in the form of graphs. Further, results of sentiment analysis of comments that determine the reaction to the video, which are encouraging

KeyWords
Hadoop, Hive, queries, Python, Machine Learning, Naïve Bayes, YouTube, Sentiment Analysis component



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