Assessing sentiment of text by semantic dependency and contextual valence analysis

Mostafa Al Masum Shaikh*, Helmut Prendinger, Ishizuka Mitsuru

*この研究の対応する著者

研究成果

56 被引用数 (Scopus)

抄録

Text is not only an important medium to describe facts and events, but also to effectively communicate information about the writer's (positive or negative) sentiment underlying an opinion, and an affect or emotion (e.g. happy, fearful, surprised etc.). We consider sentiment assessment and emotion sensing from text as two different problems, whereby sentiment assessment is a prior task to emotion sensing. This paper presents an approach to sentiment assessment, i.e. the recognition of negative or positive sense of a sentence. We perform semantic dependency analysis on the semantic verb frames of each sentence, and apply a set of rules to each dependency relation to calculate the contextual valence of the whole sentence. By employing a domain-independent, rule-based approach, our system is able to automatically identify sentence-level sentiment. Empirical results indicate that our system outperforms another state-of-the-art approach.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ191-202
ページ数12
4738 LNCS
出版ステータスPublished - 2007
外部発表はい
イベント2nd International Conference on Affective Computing and Intelligent Interaction, ACII 2007 - Lisbon
継続期間: 2007 9 122007 9 14

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4738 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other2nd International Conference on Affective Computing and Intelligent Interaction, ACII 2007
CityLisbon
Period07/9/1207/9/14

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 生化学、遺伝学、分子生物学(全般)
  • 理論的コンピュータサイエンス

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