Emoticon analysis for Chinese health and fitness topics

Shuo Yu, Hongyi Zhu, Shan Jiang, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


An emoticon is a metacommunicative pictorial representation of facial expressions, which serves to convey information about the sender's emotional state. To complement non-verbal communication, emoticons are frequently used in Chinese online social media, especially in discussions of health and fitness topics. However, limited research has been done to effectively analyze emoticons in a Chinese context. In this study, we developed an emoticon analysis system to extract emoticons from Chinese text and classify them into one of 7 affect categories. The system is based on a kinesics model which divides emoticons into semantic areas (eyes, mouths, etc.), with an improvement for adaption in the Chinese context. Empirical tests were conducted to evaluate the effectiveness of the proposed system in extracting and classifying emoticons, based on a corpus of more than one million sentences of Chinese health- and fitness-related online messages. Results showed the system to be effective in detecting and extracting emoticons from text, and in interpreting the emotion conveyed by emoticons.

Original languageEnglish (US)
Title of host publicationSmart Health - International Conference, ICSH 2014, Proceedings
Number of pages12
ISBN (Print)9783319084152
StatePublished - 2014
Event2nd International Conference for Smart Health, CSH 2014 - Beijing, China
Duration: Jul 10 2014Jul 11 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8549 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2nd International Conference for Smart Health, CSH 2014


  • Affect Analysis
  • Emoticon
  • Health and Fitness

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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