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 |
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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. |
doi_str_mv | 10.1007/s10115-020-01497-6 |
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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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