NDLI: Subjective Document Classification Using Network Analysis

Content Provider	IEEE Xplore Digital Library
Author	Minkyoung Kim Byoung-Tak Zhang Lee, J.-S.
Copyright Year	2010
Abstract	Network analysis methods have been applied in many areas such as computer science, social science, biology and physics. In this paper, we apply network analysis methods to the linguistic domain for classifying subjective documents. Particularly, we view that subjective documents are related to one another according to some common subjective words and build a subjective document network of which nodes are documents and of which links represent the similarity between two documents. In addition, we consider that adjectives and adverbs are the two representatives carrying sentimental polarities among parts-of-speeches, and perform experiments for three cases, using adjectives only, adverbs only, and both adjectives and adverbs together. In conclusion, this paper proposes a new method to the subjective document classification problem by applying network analysis methods without requiring linguistic domain knowledge and suggests the possibility of detecting themes among documents rather than binary classification.
Starting Page	365
Ending Page	369
File Size	2376821
Page Count	5
File Format	PDF
ISBN	9781424477876
DOI	10.1109/ASONAM.2010.65
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-09
Publisher Place	Denmark
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models Accuracy subjective document classification Communities Training data Motion pictures Data models network analysis Pragmatics
Content Type	Text
Resource Type	Article

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