A review of literature on the use of machine learning methods for opinion mining

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dc.contributor.authorOnan, A
dc.contributor.authorKorukoglu, S
dc.date.accessioned2024-07-18T12:00:28Z
dc.date.available2024-07-18T12:00:28Z
dc.description.abstractOpinion mining is an emerging field which uses methods of natural language processing, text mining and computational linguistics to extract subjective information of opinion holders. Opinion mining can be viewed as a classification problem. Hence, machine learning based methods are widely employed for sentiment classification. Machine learning based methods in opinion mining can be mainly classified as supervised, semi-supervised and unsupervised methods. In this study, main existing literature on the use of machine learning methods for opinion mining has been presented. Besides, the weak and strong characteristics of machine learning methods have been discussed.
dc.identifier.issn1300-7009
dc.identifier.other2147-5881
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/7738
dc.language.isoTurkish
dc.publisherPAMUKKALE UNIV
dc.subjectLINGUAL SENTIMENT CLASSIFICATION
dc.subjectALGORITHMS
dc.subjectLEXICON
dc.titleA review of literature on the use of machine learning methods for opinion mining
dc.typeReview

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