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Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm
2018
PLoS ONE
Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with
doi:10.1371/journal.pone.0194852
pmid:29684036
pmcid:PMC5912726
fatcat:hjyygmdjv5bjdpdjnt6ibckrcm