Sentence Subjectivity Analysis in Social Domains

Subjectivity analysis recognizes the contextual polarity of opinions, attitudes, emotions, feelings etc. regarding products, services, topics, or issues. Subjectivity classification categorizes the given text as subjective or objective. While an objective text contains one or more facts about a product or an issue, a subjective text expresses author´s opinions. Statistical analysis shows that subjectivity analysis of social issues is different from that of products. This paper focuses on subjectivity analysis of social issues. Subjectivity of a document strongly depends on its sentences. Hence, a lexical-syntactical approach is proposed to recognize and classify subjectivity at the sentence level. This approach considers the role of various opinion terms especially verbs on opinions regarding social issues. Evaluation of the proposed approach on a data-set consisting comments about abortion shows that it slightly outperforms other similar works. It has a good accuracy especially on the strong sentences which express explicit opinions. Its reasonable F-measure demonstrates a good balance between the precision and recall which makes it suitable for applications such as sentiment polarity classification, text sentiment summarization, and opinion question answering.