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Social Network Analysis and Mining

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01.12.2021 | Review Paper

A review on sentiment analysis and emotion detection from text

verfasst von: Pansy Nandwani, Rupali Verma

Erschienen in: Social Network Analysis and Mining | Ausgabe 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.

Vorheriger Artikel Social network analysis using deep learning: applications and schemes

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Titel: A review on sentiment analysis and emotion detection from text
verfasst von: Pansy Nandwani
Rupali Verma
Publikationsdatum: 01.12.2021
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2021
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-021-00776-6

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