Sentiment lexicons and non-English languages: a survey

The ever-increasing number of Internet users and online services, such as Amazon, Twitter and Facebook has rapidly motivated people to not just transact using the Internet but to also voice their opinions about products, services, policies, etc. Sentiment analysis is a field of study to extract and...

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Veröffentlicht in:Knowledge and information systems 2020-12, Vol.62 (12), p.4445-4480
Hauptverfasser: Kaity, Mohammed, Balakrishnan, Vimala
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description The ever-increasing number of Internet users and online services, such as Amazon, Twitter and Facebook has rapidly motivated people to not just transact using the Internet but to also voice their opinions about products, services, policies, etc. Sentiment analysis is a field of study to extract and analyze public views and opinions. However, current research within this field mainly focuses on building systems and resources using the English language. The primary objective of this study is to examine existing research in building sentiment lexicon systems and to classify the methods with respect to non-English datasets. Additionally, the study also reviewed the tools used to build sentiment lexicons for non-English languages, ranging from those using machine translation to graph-based methods. Shortcomings are highlighted with the approaches along with recommendations to improve the performance of each approach and areas for further study and research.
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subjects Computer Science
Data mining
Data Mining and Knowledge Discovery
Database Management
English language
Information Storage and Retrieval
Information Systems and Communication Service
Information Systems Applications (incl.Internet)
Internet
IT in Business
Languages
Machine translation
Non-English languages
Sentiment analysis
Survey Paper
title Sentiment lexicons and non-English languages: a survey
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