Lexical-syntactical patterns for subjectivity analysis of social issues

Abstract

Subjectivity analysis investigates attitudes, feelings, and expressed opinions about products, services, topics, or issues. As the basic task, it classifies a text as subjective or objective. While subjective text expresses opinions about an object or issue using sentiment expressions, objective text describes an object or issue considering their facts. The presence of sentiment terms such as adjectives, nouns and adverbs in products reviews usually implicates their subjectivity, but for comments about social issues, it is more complicated and sentiment phrases and patterns are more common and descriptive. This paper proposes a lexical-syntactical structure for subjective patterns for subjectivity analysis in social domains. It is employed and evaluated for subjectivity and sentiment classification at the sentence level. The proposed method outperforms some similar works. Moreover, its reasonable F-measure implicates its usability in applications like sentiment summarization and opinion question answering. © Springer International Publishing 2013.