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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >
CAO : A Fully Automatic Emoticon Analysis System
| Title: | CAO : A Fully Automatic Emoticon Analysis System |
| Authors: | Ptaszynski, Michal Browse this author | | Maciejewski, Jacek Browse this author | | Dybala, Pawel Browse this author | | Rzepka, Rafal Browse this author →KAKEN DB | | Araki, Kenji Browse this author |
| Issue Date: | 2010 |
| Publisher: | AAAI |
| Journal Title: | Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10) |
| Start Page: | 1026 |
| End Page: | 1032 |
| Abstract: | This paper presents CAO, a system for affect analysis of emoticons. Emoticons are strings of symbols widely used in text-based online communication to convey emotions. It extracts emoticons from input and determines specific emotions they express. Firstly, by matching the extracted emoticons to a raw emoticon database, containing over ten thousand emoticon samples extracted from the Web and annotated automatically. The emoticons for which emotion types could not be determined using only this database, are automatically divided into semantic areas representing "mouths" or "eyes", based on the theory of kinesics. The areas are automatically annotated according to their co-occurrence in the database. The annotation is firstly based on the eyemouth- eye triplet, and if no such triplet is found, all semantic areas are estimated separately. This provides the system coverage exceeding 3 million possibilities. The evaluation, performed on both training and test sets, confirmed the system's capability to sufficiently detect and extract any emoticon, analyze its semantic structure and estimate the potential emotion types expressed. The system achieved nearly ideal scores, outperforming existing emoticon analysis systems. |
| Conference Name: | AAAI Conference on Artificial Intelligence |
| Conference Sequence: | 24 |
| Conference Place: | Atlanta, Georgia |
| Type: | proceedings |
| URI: | http://hdl.handle.net/2115/63633 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: RZEPKA Rafal
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