A comprehensive survey on sentiment analysis: Approaches, challenges and trends

Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people’s opinions, sentiments, attitudes, perceptions, etc., toward different entities such as topics, products, and services. The fast evolution of Internet-based applications like websites, social netw...

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Published in:Knowledge-based systems Vol. 226; p. 107134
Main Authors: Birjali, Marouane, Kasri, Mohammed, Beni-Hssane, Abderrahim
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 17.08.2021
Elsevier Science Ltd
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ISSN:0950-7051, 1872-7409
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Abstract Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people’s opinions, sentiments, attitudes, perceptions, etc., toward different entities such as topics, products, and services. The fast evolution of Internet-based applications like websites, social networks, and blogs, leads people to generate enormous heaps of opinions and reviews about products, services, and day-to-day activities. Sentiment analysis poses as a powerful tool for businesses, governments, and researchers to extract and analyze public mood and views, gain business insight, and make better decisions. This paper presents a complete study of sentiment analysis approaches, challenges, and trends, to give researchers a global survey on sentiment analysis and its related fields. The paper presents the applications of sentiment analysis and describes the generic process of this task. Then, it reviews, compares, and investigates the used approaches to have an exhaustive view of their advantages and drawbacks. The challenges of sentiment analysis are discussed next to clarify future directions. •Sentiment analysis is constantly evolving through approaches, data and models.•The paper provides an unprecedented and comprehensive survey on sentiment analysis.•Traditional and recent models are discussed, compared and classified.•Pointing out the reasons to select the proper model for sentiment analysis.•The paper summarizes the sentiment analysis models to monitor future trends.
AbstractList Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people’s opinions, sentiments, attitudes, perceptions, etc., toward different entities such as topics, products, and services. The fast evolution of Internet-based applications like websites, social networks, and blogs, leads people to generate enormous heaps of opinions and reviews about products, services, and day-to-day activities. Sentiment analysis poses as a powerful tool for businesses, governments, and researchers to extract and analyze public mood and views, gain business insight, and make better decisions. This paper presents a complete study of sentiment analysis approaches, challenges, and trends, to give researchers a global survey on sentiment analysis and its related fields. The paper presents the applications of sentiment analysis and describes the generic process of this task. Then, it reviews, compares, and investigates the used approaches to have an exhaustive view of their advantages and drawbacks. The challenges of sentiment analysis are discussed next to clarify future directions. •Sentiment analysis is constantly evolving through approaches, data and models.•The paper provides an unprecedented and comprehensive survey on sentiment analysis.•Traditional and recent models are discussed, compared and classified.•Pointing out the reasons to select the proper model for sentiment analysis.•The paper summarizes the sentiment analysis models to monitor future trends.
Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities such as topics, products, and services. The fast evolution of Internet-based applications like websites, social networks, and blogs, leads people to generate enormous heaps of opinions and reviews about products, services, and day-to-day activities. Sentiment analysis poses as a powerful tool for businesses, governments, and researchers to extract and analyze public mood and views, gain business insight, and make better decisions. This paper presents a complete study of sentiment analysis approaches, challenges, and trends, to give researchers a global survey on sentiment analysis and its related fields. The paper presents the applications of sentiment analysis and describes the generic process of this task. Then, it reviews, compares, and investigates the used approaches to have an exhaustive view of their advantages and drawbacks. The challenges of sentiment analysis are discussed next to clarify future directions.
ArticleNumber 107134
Author Birjali, Marouane
Kasri, Mohammed
Beni-Hssane, Abderrahim
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  givenname: Mohammed
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  givenname: Abderrahim
  surname: Beni-Hssane
  fullname: Beni-Hssane, Abderrahim
  email: abenihssane@yahoo.fr
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Keywords Deep learning
Sentiment analysis
Opinion mining
Lexicon-based
Machine learning
Sentiment classification
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SSID ssj0002218
Score 2.701742
Snippet Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people’s opinions, sentiments, attitudes, perceptions, etc.,...
Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people's opinions, sentiments, attitudes, perceptions, etc.,...
SourceID proquest
crossref
elsevier
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 107134
SubjectTerms Analysis
Attitudes
Blogs
Data mining
Decision analysis
Deep learning
Emotions
Internet
Lexicon-based
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Sentiment classification
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Title A comprehensive survey on sentiment analysis: Approaches, challenges and trends
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