WordNet: a lexical database for English
Communications of the ACM
Ultraconservative online algorithms for multiclass problems
The Journal of Machine Learning Research
Partial parsing via finite-state cascades
Natural Language Engineering
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on 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
Structure compilation: trading structure for features
Proceedings of the 25th international conference on Machine learning
SemEval-2007 task 14: affective text
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Discovering voter preferences in blogs using mixtures of topic models
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
The effect of negation on sentiment analysis and retrieval effectiveness
Proceedings of the 18th ACM conference on Information and knowledge management
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Dependency tree-based sentiment classification using CRFs with hidden variables
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Hierarchical sequential learning for extracting opinions and their attributes
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
A survey on the role of negation in sentiment analysis
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
AM: textual attitude analysis model
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Classification of Dreams Using Machine Learning
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Opinion identification in Spanish texts
YIWCALA '10 Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas
Incorporating content structure into text analysis applications
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Multi-level structured models for document-level sentiment classification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Recognition of affect, judgment, and appreciation in text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Which clustering do you want? inducing your ideal clustering with minimal feedback
Journal of Artificial Intelligence Research
Affect analysis model: Novel rule-based approach to affect sensing from text
Natural Language Engineering
Joint bilingual sentiment classification with unlabeled parallel corpora
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Extracting social power relationships from natural language
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Extracting opinion expressions and their polarities: exploration of pipelines and joint models
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
A verb lexicon model for deep sentiment analysis and opinion mining applications
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Semi-supervised recursive autoencoders for predicting sentiment distributions
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Compositional matrix-space models for sentiment analysis
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Lexicon-based Comments-oriented News Sentiment Analyzer system
Expert Systems with Applications: An International Journal
A generate-and-test method of detecting negative-sentiment sentences
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Building subjectivity lexicon(s) from scratch for essay data
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Sentiment analysis on twitter data for portuguese language
PROPOR'12 Proceedings of the 10th international conference on Computational Processing of the Portuguese Language
Entity-centric topic-oriented opinion summarization in twitter
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
A generic approach to generate opinion lists of phrases for opinion mining applications
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Sentiment identification by incorporating syntax, semantics and context information
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
A lexicon model for deep sentiment analysis and opinion mining applications
Decision Support Systems
That is your evidence?: Classifying stance in online political debate
Decision Support Systems
How do negation and modality impact on opinions?
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
POLITICAL-ADS: an annotated corpus of event-level evaluativity
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
Damping sentiment analysis in online communication: discussions, monologs and dialogs
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Sentiment profiles of multiword expressions in test-taker essays: The case of noun-noun compounds
ACM Transactions on Speech and Language Processing (TSLP) - Special issue on multiword expressions: From theory to practice and use, part 2
A probabilistic graphical model for brand reputation assessment in social networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Enhancing sentiment extraction from text by means of arguments
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
Evaluation of an algorithm for aspect-based opinion mining using a lexicon-based approach
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
Bootstrapping polarity classifiers with rule-based classification
Language Resources and Evaluation
Associating targets with SentiUnits: a step forward in sentiment analysis of Urdu text
Artificial Intelligence Review
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Determining the polarity of a sentiment-bearing expression requires more than a simple bag-of-words approach. In particular, words or constituents within the expression can interact with each other to yield a particular overall polarity. In this paper, we view such subsentential interactions in light of compositional semantics, and present a novel learning-based approach that incorporates structural inference motivated by compositional semantics into the learning procedure. Our experiments show that (1) simple heuristics based on compositional semantics can perform better than learning-based methods that do not incorporate compositional semantics (accuracy of 89.7% vs. 89.1%), but (2) a method that integrates compositional semantics into learning performs better than all other alternatives (90.7%). We also find that "content-word negators", not widely employed in previous work, play an important role in determining expression-level polarity. Finally, in contrast to conventional wisdom, we find that expression-level classification accuracy uniformly decreases as additional, potentially disambiguating, context is considered.