Building word-emotion mapping dictionary for online news

Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal

11 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)28-39
Journal / PublicationCEUR Workshop Proceedings
Volume917
Publication statusPublished - 2012

Conference

Title1st International Workshop on Sentiment Discovery from Affective Data 2012, SDAD 2012 - In Conjunction with ECML-PKDD 2012
PlaceUnited Kingdom
CityBristol
Period28 September 2012

Abstract

Sentiment analysis of online documents such as news articles, blogs and microblogs has received increasing attention. We propose an efficient method of automatically building the word-emotion mapping dictionary for social emotion detection. In the dictionary, each word is associated with the distribution on a series of human emotions. In addition, three different pruning strategies are proposed to refine the dictionary. Experiment on the real-world data sets has validated the effectiveness and reliability of the method. Compared with other lexicons, the dictionary generated using our approach is more adaptive for personalized data set, language-independent, fine-grained, and volume-unlimited. The generated dictionary has a wide range of applications, including predicting the emotional distribution of news articles and tracking the change of social emotions on certain events over time.

Research Area(s)

  • Emotion dictionary, Maximum likelihood estimation, Social emotion detection

Citation Format(s)

Building word-emotion mapping dictionary for online news. / Rao, Yanghui; Quan, Xiaojun; Wenyin, Liu et al.
In: CEUR Workshop Proceedings, Vol. 917, 2012, p. 28-39.

Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal