Authors:
Yoshimi Suzuki
and
Fumiyo Fukumoto
Affiliation:
University of Yamanashi, Japan
Keyword(s):
Opinion Extraction, Editorial Articles.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Pattern Recognition
;
Symbolic Systems
Abstract:
Opinion extraction supports various tasks such as sentiment analysis in user reviews for recommendations
and editorial summarization. In this paper, we address the problem of opinion extraction from newspaper
editorials. To extract author’s opinion, we used context information addition to the features within a single
sentence only. Context information are a location of the target sentence, and its preceding, and succeeding
sentences. We defined the opinion extraction task as a sequence labeling problem, using conditional random
fields (CRF). We used Japanese newspaper editorials in the experiments, and used multiple combination of
features of CRF to reveal which features are effective for opinion extraction. The experimental results show
the effectiveness of the method, especially, predicate expression, location and previous sentence are effective
for opinion extraction.