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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Knowledge-based systems Ročník 226; s. 107134
Hlavní autoři: Birjali, Marouane, Kasri, Mohammed, Beni-Hssane, Abderrahim
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 17.08.2021
Elsevier Science Ltd
Témata:
Analysis
Attitudes
Blogs
Data mining
Decision analysis
Deep learning
Emotions
Internet
Lexicon-based
Machine learning
Opinion mining
Polls & surveys
Sentiment analysis
Sentiment classification
Social networks
Trends
Websites
Deep learning
Sentiment analysis
Opinion mining
Lexicon-based
Machine learning
Sentiment classification
ISSN:0950-7051, 1872-7409
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2021.107134