- 著者
- Michal PTASZYNSKI Pawel DYBALA Wenhan SHI Rafal RZEPKA Kenji ARAKI
- 出版者
- Japan Society for Fuzzy Theory and Intelligent Informatics
- 雑誌
- 知能と情報 (ISSN:13477986)
- 巻号頁・発行日
- vol.21, no.2, pp.194-213, 2009-04-15 (Released:2009-06-30)
- 参考文献数
- 63
- 被引用文献数
- 7 19
We propose a method for affect analysis of textual input in Japanese supported with Web mining. The method is based on a pragmatic reasoning that emotional states of a speaker are conveyed by emotional expressions used in emotive utterances. It means that if an emotive expression is used in a sentence in a context described as emotive, the emotion conveyed in the text is revealed by the used emotive expression. The system ML-Ask (Emotive Elements / Expressions Analysis System) is constructed on the basis of this idea. An evaluation of the system is performed in which two evaluation methods are compared. To choose the most objective evaluation method we compare the most popular method in the field and a method proposed by us. The proposed evaluation method was shown to be more objective and revealed the strong and weak points of the system in detail. In the evaluation experiment ML-Ask reached human level in recognizing the general emotiveness of an utterance (0.83 balanced F-score) and 63% of human level in recognizing the specific types of emotions. We support the system with a Web mining technique to improve the performance of emotional state types extraction. In the Web mining technique emotive associations are extracted from the Web using co-occurrences of emotive expressions with morphemes of causality. The Web mining technique improved the performance of the emotional states types extraction to 85% of human performance.
- 著者
- Michal Ptaszynski
- 雑誌
- 情報処理
- 巻号頁・発行日
- vol.53, no.3, pp.204-210, 2012-02-15
この記事ではまず顔文字に関する研究の学際的な調査を行う.社会科学における顔文字研究では顔文字がオンラインコミュニケーションにとって不可欠であることが確認されている.しかしながら,自然言語処理分野の視点からの研究は比較的少ない.そこで顔文字解析用ツールCAOシステムを紹介する.CAOはインターネットから収集した1万強の顔文字の感情種類別のデータベースをもとに構築され,顔文字は口や目などの部分に自動的に分割される.顔文字を分割するアイディアは,50年代頃に開発されたkinesics理論に基づいている.口と目の組み合わせ数が3百万以上のカバレッジを持ったCAOシステムは顔文字の検出,抽出,そして感情解析を正確に行うことができる.