Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
IEEE Transactions on Knowledge and Data Engineering
Data Mining
Introduction to Information Retrieval
Introduction to Information Retrieval
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ACM Transactions on Speech and Language Processing (TSLP)
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
A survey on sentiment detection of reviews
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TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
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Proceedings of the 19th international conference on World wide web
A latent variable model for geographic lexical variation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
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Proceedings of the fourth ACM international conference on Web search and data mining
Robust sentiment detection on Twitter from biased and noisy data
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Enhanced sentiment learning using Twitter hashtags and smileys
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Target-dependent Twitter sentiment classification
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Local histograms of character N-grams for authorship attribution
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
User-level sentiment analysis incorporating social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Emotional aware clustering on micro-blogging sources
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Twitter polarity classification with label propagation over lexical links and the follower graph
EMNLP '11 Proceedings of the First Workshop on Unsupervised Learning in NLP
Survey on mining subjective data on the web
Data Mining and Knowledge Discovery
Polarity analysis of micro reviews in foursquare
Proceedings of the 19th Brazilian symposium on Multimedia and the web
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Microblog content poses serious challenges to the applicability of traditional sentiment analysis and classification methods, due to its inherent characteristics. To tackle them, we introduce a method that relies on two orthogonal, but complementary sources of evidence: content-based features captured by n-gram graphs and context-based ones captured by polarity ratio. Both are language-neutral and noise-tolerant, guaranteeing high effectiveness and robustness in the settings we are considering. To ensure our approach can be integrated into practical applications with large volumes of data, we also aim at enhancing its time efficiency: we propose alternative sets of features with low extraction cost, explore dimensionality reduction and discretization techniques and experiment with multiple classification algorithms. We then evaluate our methods over a large, real-world data set extracted from Twitter, with the outcomes indicating significant improvements over the traditional techniques.