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Advanced Information Retrieval System: Theoretical and Experimental Perspective

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An Information Retrieval-Based Framework for Analysing Viewer Sentiments in YouTube Comments

Author(s): Urmila Pilania*, Manoj Kumar* and Sanjay Singh *

Pp: 39-49 (11)

DOI: 10.2174/9798898813666126010006

* (Excluding Mailing and Handling)

Abstract

The user engagement in YouTube comments could be utilized for sentiment analysis. The data is collected through web scraping from the YouTube comments. Natural Language Processing (NLP) and Bidirectional Encoder Representations from Transformers (BERT) are utilized by authors to analyze the sentiment of commenters. The current trends and user engagement in the market can be analyzed through YouTube comments. The thematic patterns are generated with the help of word clouds and sentiment distribution charts. Based on the outcome of the proposed work, it can be concluded that YouTube comments provide valuable feedback to researchers, which in turn can be used for sentiment analysis. 

Keywords: Bidirectional Encoder Representations from Transformers (BERT), Natural language processing, User engagement, YouTube comments sentiment analysis.

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