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Science of Emoticons: Research Framework and State of the Art in Analysis of kaomoji-type Emoticons
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Author(s): Michal Ptaszynski (Kitami Institute of Technology, Japan), Jacek Maciejewski (Independent Researcher, Poland), Pawel Dybala (Kotoken Language Laboratory, Poland), Rafal Rzepka (Hokkaido University, Japan), Kenji Araki (Hokkaido University, Japan)and Yoshio Momouchi (Hokkai-Gakuen University, Japan)
Copyright: 2012
Pages: 27
Source title:
Speech, Image, and Language Processing for Human Computer Interaction: Multi-Modal Advancements
Source Author(s)/Editor(s): Uma Shanker Tiwary (Indian Institute of Information Technology Allahabad, India)and Tanveer J. Siddiqui (University of Allahabad, India)
DOI: 10.4018/978-1-4666-0954-9.ch012
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Abstract
Emoticons are string of symbols representing body language in text-based communication. For a long time they have been considered as unnatural language entities. This chapter argues that, in over 40-year-long history of text-based communication, emoticons have gained a status of an indispensable means of support for text-based messages. This makes them fully a part of Natural Language Processing. The fact the emoticons have been considered as unnatural language expressions has two causes. Firstly, emoticons represent body language, which by definition is nonverbal. Secondly, there has been a lack of sufficient methods for the analysis of emoticons. Emoticons represent a multimodal (bimodal in particular) type of information. Although they are embedded in lexical form, they convey non-linguistic information. To prove this argument the authors propose that the analysis of emoticons was based on a theory designed for the analysis of body language. In particular, the authors apply the theory of kinesics to develop a state of the art system for extraction and analysis of kaomoji, Japanese emoticons. The system performance is verified in comparison with other emoticon analysis systems. Experiments showed that the presented approach provides nearly ideal results in different aspects of emoticon analysis, thus proving that emoticons possess features of multimodal expressions.
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