Analysis & Implementation of Sentiment Analysis of User YouTube Comments

EasyChair Preprint 7703

Abstract

With the turning wheel of time, the influence of the social networking websites on the people has significantly increased. People are now connecting with each other in cyber space and show their sentiments in the form of comments in different social networking websites such as Twitter, Facebook and Google Plus. YouTube is considered as a king in the field of video sharing. It is a largest video sharing repository, where people come and share their thoughts regarding video in the form of comments. “Sentiment Analysis” is the process of extracting other people's (speaker or writer) opinions from a given original source (text) utilizing natural language processing (NLP), linguistics computing, & data mining. For the interpretation of meaning of each and every comment, “text mining approach” is used. For understanding the meaningfulness of any content, it is important to classify them into positive and negative comments on the basis of user opinion. In the present study, researcher has performed sentiment analysis on YouTube comments on the most popular topics nowadays by using Classifier techniques.

Keyphrases: Classifier technique, Sentiment Analysis, Social Networking Websites, YouTube, text mining

@booklet{EasyChair:7703,
  author    = {Shivani Wadhwani and Prashant Richhariya and Anita Soni},
  title     = {Analysis & Implementation of  Sentiment Analysis of User YouTube Comments},
  howpublished = {EasyChair Preprint 7703},
  year      = {EasyChair, 2022}}