Junko Minato

Statistical analysis of a Japanese emotion corpus for natural language processing

In this paper, we build a Japanese emotion corpus and perform statistical analysis on it. We manually entered in about 1,200 example dialogue sentences. We collected statistical information from the corpus to analyze the way emotion is expressed in Japanese dialogue. Such statistics should prove useful for dealing with emotion in natural language. We believe the collected statistics accurately describe emotion in Japanese dialogue.

Corpus-based Analysis of Japanese-English Emotional Expressions

Development of information technology has increased the chances of interaction between human and computer. Understanding not only semantic information but also underlying emotion will make communication with computer more natural and congenial. As preliminary research for emotion estimation from multilingual text, we focused on emotion expressions of Japanese and English and created a corpus with about 1,200 bilingual sentences and tagged emotions on words and sentences. Based on the corpus, we statistically analyzed the characteristics of how emotions were expressed in each language and also the relationships between sentence emotion and word emotion in the sentence. The results show the characteristics of emotion expressions in Japanese and English dialogue sentences.

Determining the emotion of news articles

Authors of news stories through their choice in words and phrasing inject an underlying emotion into their stories. A story about the same event or person can have radically different emotions depending on the author, newspaper, and nationality. In this paper we propose a system to judge the emotion of a news article based on emotion word, idiom and modifier dictionaries. This type of system allows one to judge the world opinion on varying topics by looking at the emotion used within news articles about the topic.