Good location, terrible food: detecting feature sentiment in user-generated reviews
Social Network Analysis and MiningPublished 21 June 2013
Mario Cataldi, Andrea Ballatore, Ilaria Tiddi, Marie-Aude Aufaure
Citations35
SJR quartileQ1
SJR score0.62
SNIP1.41
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TL;DR
This paper presents an approach to feature-level sentiment detection that integrates natural language processing with statistical techniques, in order to extract users’ opinions about specific features of products and services from user-generated reviews.
Abstract
A growing corpus of online informal reviews is generated every day by non-experts, on social networks and blogs, about an unlimited range of products and services. Users do not only express holistic opinions, but often focus on specific features of their interest. The automatic understanding of “what people think” at the feature level can greatly support decision making, both for consumers and producers. In this paper, we present an approach to feature-level sentiment detection that integrates natural language processing with statistical techniques, in order to extract users’ opinions about specific features of products and services from user-generated reviews. First, we extract domain features, and each review is modelled as a lexical dependency graph. Second, for each review, we estimate the polarity relative to the features by leveraging the syntactic dependencies between the terms. The approach is evaluated against a ground truth consisting of set of user-generated reviews, manually annotated by 39 human subjects and available online, showing its human-like ability to capture feature-level opinions.
Keywords
Computer ScienceSocial Sciences
Language<b>WordNet: An electronic lexical database</b> . Ed. by Christiane Fellbaum. Cambridge, MA: MIT Press, 1998. Pp. xxii, 423.
11,687 Citations2000Adam Kilgarriff
The lexical database: nouns in WordNet, George A. Miller modifiers in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.
Information Processing & ManagementTerm-weighting approaches in automatic text retrieval
9,532 Citations1988Gerard Salton, Chris Buckley
This paper summarizes the insights gained in automatic term weighting, and provides baseline single term indexing models with which other more elaborate content analysis procedures can be compared.
Mining and summarizing customer reviews
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Building a Large Annotated Corpus of English: The Penn Treebank
7,528 Citations1993Mitchell P. Marcus
Thumbs up?
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now publishers, Inc. eBooksOpinion Mining and Sentiment Analysis
6,745 Citations2008Bo Pang, Lillian Lee
Foundations and Trends® in Information RetrievalOpinion Mining and Sentiment Analysis
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This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems and focuses on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis.
Journal of Marketing ResearchThe Effect of Word of Mouth on Sales: Online Book Reviews
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Meeting of the Association for Computational LinguisticsThumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
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SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining.
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Lingvisticae InvestigationesA survey of named entity recognition and classification
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1,509 Citations2003Peter D. Turney, Michael L. Littman
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Mining opinion features in customer reviews
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819 Citations1997Vasileios Hatzivassiloglou, Kathleen McKeown
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Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)An Efficient Recognition and Syntax-Analysis Algorithm for Context-Free Languages
526 Citations1965Tadao Kasami
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