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Published in: Social Network Analysis and Mining 1/2021

01-12-2021 | Review Paper

A review on sentiment analysis and emotion detection from text

Authors: Pansy Nandwani, Rupali Verma

Published in: Social Network Analysis and Mining | Issue 1/2021

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Abstract

Social networking platforms have become an essential means for communicating feelings to the entire world due to rapid expansion in the Internet era. Several people use textual content, pictures, audio, and video to express their feelings or viewpoints. Text communication via Web-based networking media, on the other hand, is somewhat overwhelming. Every second, a massive amount of unstructured data is generated on the Internet due to social media platforms. The data must be processed as rapidly as generated to comprehend human psychology, and it can be accomplished using sentiment analysis, which recognizes polarity in texts. It assesses whether the author has a negative, positive, or neutral attitude toward an item, administration, individual, or location. In some applications, sentiment analysis is insufficient and hence requires emotion detection, which determines an individual’s emotional/mental state precisely. This review paper provides understanding into levels of sentiment analysis, various emotion models, and the process of sentiment analysis and emotion detection from text. Finally, this paper discusses the challenges faced during sentiment and emotion analysis.

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Metadata
Title
A review on sentiment analysis and emotion detection from text
Authors
Pansy Nandwani
Rupali Verma
Publication date
01-12-2021
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2021
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-021-00776-6

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