Email sSentiment analysis through k-Means labeling and support vector machine classification

Liu, Sisi, and Lee, Ickjai (2018) Email sSentiment analysis through k-Means labeling and support vector machine classification. Cybernetics and Systems, 49 (3). pp. 181-199.

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Sentiment analysis for social media and online document has been a burgeoning area in text mining for the last decade. However, Email sentiment analysis has not been studied and examined thoroughly even though it is one of the most ubiquitous means of communication. In this research, a hybrid sentiment analysis framework for Email data using term frequency-inverse document frequency term weighting model for feature extraction, and k-means labeling combined with support vector machine classifier for sentiment classification is proposed. Empirical results indicate comparatively better classification results with the proposed framework than other combinations.

Item ID: 53718
Item Type: Article (Research - C1)
ISSN: 1087-6553
Keywords: email sentiment analysis; k-means labeling; support vector machine classification
Date Deposited: 12 Jul 2018 01:53
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460502 Data mining and knowledge discovery @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890299 Computer Software and Services not elsewhere classified @ 100%
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