Sentiment clustering with topic and temporal information from large email dataset

Liu, Sisi, Cai, Guochen, and Lee, Ickjai (2016) Sentiment clustering with topic and temporal information from large email dataset. In: 29th Pacific Asia Conference on Language, Information and Computation. Y16-3007. pp. 363-371. From: PACLIC 30: 30th Pacific Asia Conference on Language, Information and Computation, 28-30 October 2016, Seoul, South Korea.

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Abstract

Sentiment analysis with features addition to opinion words has been an appealing area in recent studies. Some research has been conducted for finding relationship between sentiments, topics and temporal sentiment analysis. Nevertheless, Email sentiment analysis received relatively less attention due to the complexity of its structure and indirectness of its language. This paper introduces a systematic framework for sentiment clustering using topic and temporal features for large Email datasets. Interesting Email and sentiment distribution patterns are summarized and discussed with empirical results.

Item ID: 47547
Item Type: Conference Item (Research - E1)
ISBN: 978-1-5108-3466-8
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Date Deposited: 09 Mar 2017 00:19
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 100%
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