DocumentCode :
2936884
Title :
Visual Analysis of Conflicting Opinions
Author :
Chen, Chaomei ; Ibekwe-SanJuan, F. ; SanJuan, Eric ; Weaver, Chris
Author_Institution :
Drexel Univ., Philadelphia, PA
fYear :
2006
fDate :
Oct. 31 2006-Nov. 2 2006
Firstpage :
59
Lastpage :
66
Abstract :
Understanding the nature and dynamics of conflicting opinions is a profound and challenging issue. In this paper we address several aspects of the issue through a study of more than 3,000 Amazon customer reviews of the controversial bestseller The Da Vinci Code, including 1,738 positive and 918 negative reviews. The study is motivated by critical questions such as: what are the differences between positive and negative reviews? What is the origin of a particular opinion? How do these opinions change over time? To what extent can differentiating features be identified from unstructured text? How accurately can these features predict the category of a review? We first analyze terminology variations in these reviews in terms of syntactic, semantic, and statistic associations identified by TermWatch and use term variation patterns to depict underlying topics. We then select the most predictive terms based on log likelihood tests and demonstrate that this small set of terms classifies over 70% of the conflicting reviews correctly. This feature selection process reduces the dimensionality of the feature space from more than 20,000 dimensions to a couple of hundreds. We utilize automatically generated decision trees to facilitate the understanding of conflicting opinions in terms of these highly predictive terms. This study also uses a number of visualization and modeling tools to identify not only what positive and negative reviews have in common, but also they differ and evolve over time
Keywords :
classification; computational linguistics; data visualisation; decision trees; The Da Vinci Code; conflicting opinion; conflicting reviews; decision tree; feature selection process; feature space dimensionality reduction; log likelihood test; negative reviews; positive reviews; predictive term; semantic analysis; statistic association analysis; syntactic analysis; term variation pattern; terminology variation analysis; visual analysis; visualization tool; Chaos; Chromium; Decision trees; Pattern analysis; Statistical analysis; Terminology; Testing; User interfaces; Visual analytics; Visualization; Visual analytics; conflicting opinions; decision tree; predictive text analysis; sense making; terminology variation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Analytics Science And Technology, 2006 IEEE Symposium On
Conference_Location :
Baltimore, MD
Print_ISBN :
1-4244-0591-2
Electronic_ISBN :
1-4244-0592-0
Type :
conf
DOI :
10.1109/VAST.2006.261431
Filename :
4035748
Link To Document :
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