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survey

Current State of Text Sentiment Analysis from Opinion to Emotion Mining

Authors:

Ameneh Gholipour Shahraki,

Osmar R. ZaianeAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 50, Issue 2

Article No.: 25, Pages 1 - 33

https://doi.org/10.1145/3057270

Published: 25 May 2017 Publication History

Abstract

Sentiment analysis from text consists of extracting information about opinions, sentiments, and even emotions conveyed by writers towards topics of interest. It is often equated to opinion mining, but it should also encompass emotion mining. Opinion mining involves the use of natural language processing and machine learning to determine the attitude of a writer towards a subject. Emotion mining is also using similar technologies but is concerned with detecting and classifying writers emotions toward events or topics. Textual emotion-mining methods have various applications, including gaining information about customer satisfaction, helping in selecting teaching materials in e-learning, recommending products based on users emotions, and even predicting mental-health disorders. In surveys on sentiment analysis, which are often old or incomplete, the strong link between opinion mining and emotion mining is understated. This motivates the need for a different and new perspective on the literature on sentiment analysis, with a focus on emotion mining. We present the state-of-the-art methods and propose the following contributions: (1) a taxonomy of sentiment analysis; (2) a survey on polarity classification methods and resources, especially those related to emotion mining; (3) a complete survey on emotion theories and emotion-mining research; and (4) some useful resources, including lexicons and datasets.

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Cited By

Ma FYuan YXie YRen HLiu IHe YRen FYu FNi S(2025)Generative technology for human emotion recognition: A scoping reviewInformation Fusion10.1016/j.inffus.2024.102753115(102753)Online publication date: Mar-2025
https://doi.org/10.1016/j.inffus.2024.102753
Shi XYang MHu MRen FKang XDing W(2025)Affective knowledge assisted bi-directional learning for Multi-modal Aspect-based Sentiment AnalysisComputer Speech & Language10.1016/j.csl.2024.10175591(101755)Online publication date: Apr-2025
https://doi.org/10.1016/j.csl.2024.101755
Mills B(2024)Analysing Language-Based Cyber Threats: An Examination of Cybersecurity for Chinese TextThe Pinnacle: A Journal by Scholar-Practitioners10.61643/c785332:1Online publication date: Mar-2024
https://doi.org/10.61643/c78533
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Index Terms

Current State of Text Sentiment Analysis from Opinion to Emotion Mining
1. General and reference
  1. Document types
    1. Surveys and overviews
2. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 50, Issue 2

March 2018

567 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3071073

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL 32611

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Copyright © 2017 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 May 2017

Accepted: 01 February 2017

Revised: 01 October 2016

Received: 01 August 2015

Published in CSUR Volume 50, Issue 2

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Ma FYuan YXie YRen HLiu IHe YRen FYu FNi S(2025)Generative technology for human emotion recognition: A scoping reviewInformation Fusion10.1016/j.inffus.2024.102753115(102753)Online publication date: Mar-2025
https://doi.org/10.1016/j.inffus.2024.102753
Shi XYang MHu MRen FKang XDing W(2025)Affective knowledge assisted bi-directional learning for Multi-modal Aspect-based Sentiment AnalysisComputer Speech & Language10.1016/j.csl.2024.10175591(101755)Online publication date: Apr-2025
https://doi.org/10.1016/j.csl.2024.101755
Mills B(2024)Analysing Language-Based Cyber Threats: An Examination of Cybersecurity for Chinese TextThe Pinnacle: A Journal by Scholar-Practitioners10.61643/c785332:1Online publication date: Mar-2024
https://doi.org/10.61643/c78533
Om Kumar CBalakannan BMarappan SRavi KGajendran SGunasekaran T(2024)Quantum Machine Learning Architecture for EEG-Based Emotion RecognitionHarnessing Quantum Cryptography for Next-Generation Security Solutions10.4018/979-8-3693-9220-1.ch006(153-180)Online publication date: 27-Sep-2024
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Farokhnia Hamedani MEsmaeili MSun YSheybani EJavidi G(2024)Paving the way for COVID survivors’ psychosocial rehabilitation: Mining topics, sentiments, and their trajectories over time from RedditHealth Informatics Journal10.1177/1460458224124068030:2Online publication date: 13-May-2024
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Zhang LMu X(2024)Tweets on a horror movieJournal of Information Science10.1177/0165551522111651650:5(1085-1097)Online publication date: 1-Oct-2024
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