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2021 | OriginalPaper | Chapter

The Sentimental Analysis of Social Media Data: A Survey

Authors : Vartika Bhadana, Hitendra Garg

Published in: Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Publisher: Springer Singapore

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Abstract

Nowadays, machine learning plays a very important role in every field. For recommendation systems, user feedback is relevant because they contain different forms of emotional details that may affect the reliability or consistency of the recommendation. Online reviews, comments are very helpful in selecting the said items and services as it gives real feedback about the quality of these items and services. The categorizations of these items based on feedback provided by actual users are known as sentimental analysis. In this study, we described various machine learning techniques and parameters used for the sentimental analysis of reviews, comments, and feedback available on health care, Facebook, Twitter, and other social media networking sites. The study reveals that the most commonly used approaches are machine learning and deep learning.

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Title: The Sentimental Analysis of Social Media Data: A Survey
Authors: Vartika Bhadana
Hitendra Garg
Publisher: Springer Singapore
Book: Proceedings of Second International Conference on Computing, Communications, and Cyber-Security
Print ISBN: 978-981-16-0732-5

Electronic ISBN: 978-981-16-0733-2

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-981-16-0733-2_17

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