Linguistic Features for Subjectivity Classification

• Published in: 2012 International Conference on Asian Language Processing (IALP) pp. 17 - 20
• Main Authors: Huong Nguyen Thi Xuan, Anh Cuong Le, Le Minh Nguyen
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.11.2012
• Subjects: Accuracy; Computational linguistics; Data mining; Feature extraction; Motion pictures; opinion mining; Pragmatics; sentiment analysis; subjectivity classification; Syntactics
• ISBN: 9781467361132; 1467361135
• DOI: 10.1109/IALP.2012.47

Opinions are subjective expressions that describe people's viewpoints, perspectives or feelings about entities, events and theirs properties. Detecting subjective expressions is the task of identifying whether a given text is subjective (i.e. an opinion)or objective (i.e. a reports fact). This task is considered as the first problem and it is very important for opinion mining and sentiment analysis which is now attracting many researchers cause its applicable capacity. Improvements in subjectivity classification will positively impact on the performance of a sentiment analysis system. Actually, features play the most important role for getting accurate subjective sentences. In this paper, we will enrich features by using syntactic information of the text. From our observation when investigating opinion evidences in the texts, we will propose syntax-based patterns which are used for extracting rich linguistic features. Combining these new features with conventional features from previous studies, we obtain a high accuracy (about 92.1%) for detecting subjective sentences on the Movie review data.