WordNet: a lexical database for English
Communications of the ACM
Automatic query wefinement using lexical affinities with maximal information gain
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Argument based machine learning applied to law
Artificial Intelligence and Law - Argumentation in artificial intelligence and law
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Identifying sources of opinions with conditional random fields and extraction patterns
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
OpinionFinder: a system for subjectivity analysis
HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations
Argumentation in artificial intelligence
Artificial Intelligence
Argument based machine learning
Artificial Intelligence
Freebase: a collaboratively created graph database for structuring human knowledge
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Learning with compositional semantics as structural inference for subsentential sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Identifying expressions of opinion in context
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A survey of paraphrasing and textual entailment methods
Journal of Artificial Intelligence Research
The changing science of machine learning
Machine Learning
Artificial Intelligence and Law
Detecting implicit expressions of sentiment in text based on commonsense knowledge
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Full Spectrum Opinion Mining: Integrating Domain, Syntactic and Lexical Knowledge
ICDMW '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining Workshops
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Sentiment Analysis is concerned with (1) differentiating opinionated text from factual text and, in the case of opinionated text, (2) determine its polarity. With this paper, we address problem (1) and present A-SVM (Argument enhanced Support Vector Machines), a multimodal system that focuses on the discrimination of opinionated text from non-opinionated text with the help of (i) Support Vector Machines (SVM) and (ii) arguments, acquired by means of a user feedback mechanism, and used to improve the SVM classifications. We have used a prototype to investigate the validity of approaching Sentiment Analysis in this multi faceted manner by comparing straightforward Machine Learning techniques with our multimodal system architecture. All evaluations were executed using a purpose-built corpus of annotated text and A-SVM's classification performance was compared to that of SVM. The classification of a test set of approximately 4,500 n-grams yielded an increase in classification precision of 5.6%.