A vector space model for automatic indexing
Communications of the ACM
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Determining the semantic orientation of terms through gloss classification
Proceedings of the 14th ACM international conference on Information and knowledge management
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
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
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
An empirical approach for opinion detection using significant sentences
AMT'10 Proceedings of the 6th international conference on Active media technology
Pattern and keyword based opinion analysis from opinionated texts
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Detection of web users' opinion from multimodal opinion elements
COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
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In this paper we present a sentiment dictionary that aids in identifying subjective phrases from opinionated texts useful for opinion detection approaches in determining opinion of web users from opinionated texts. Web users document their opinion on diverse topics using variety of mediums available in the web. These opinions will be very useful to other web users that assist them to change their perspective or take a few useful decisions. Today, opinions are expressed by web users using multimodal opinion elements like normal phrases, emoticons and short words or sms language. To capture web users opinion with multimodal opinion elements, we need dictionaries that will assist in identifying these multimodal opinion phrases. Dictionaries mentioned in literatures are less useful in identifying multi modal subjective phrases and opinion of web users. We examine a number of dictionaries and propose an effective sentiment dictionary useful in identifying subjective phrases and opinion of web users on products. The result obtained indicates the proposed sentiment dictionary is effective in mining multimodal user opinion.