Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
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
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
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
Annotating attributions and private states
CorpusAnno '05 Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky
FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Learning to identify emotions in text
Proceedings of the 2008 ACM symposium on Applied computing
Emotion classification using massive examples extracted from the web
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
A cognitive-based annotation system for emotion computing
ACL-IJCNLP '09 Proceedings of the Third Linguistic Annotation Workshop
International Journal of Human-Computer Studies
A text-driven rule-based system for emotion cause detection
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
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
Hierarchical versus flat classification of emotions in text
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
Recognition of affect, judgment, and appreciation in text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Affect analysis model: Novel rule-based approach to affect sensing from text
Natural Language Engineering
Hierarchical approach to emotion recognition and classification in texts
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Detecting implicit expressions of emotion in text: A comparative analysis
Decision Support Systems
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Prior versus contextual emotion of a word in a sentence
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
Analyzing emotional states induced by news articles with latent semantic analysis
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
Unsupervised Emotion Detection from Text Using Semantic and Syntactic Relations
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Using google n-grams to expand word-emotion association lexicon
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Evaluating the impact of syntax and semantics on emotion recognition from text
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Prior and contextual emotion of words in sentential context
Computer Speech and Language
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This paper presents a headline emotion classification approach based on frequency and co-occurrence information collected from the World Wide Web. The content words of a headline (nouns, verbs, adverbs and adjectives) are extracted in order to form different bag of word pairs with the joy, disgust, fear, anger, sadness and surprise emotions. For each pair, we compute the Mutual Information Score which is obtained from the web occurrences of an emotion and the content words. Our approach is based on the hypothesis that group of words which co-occur together across many documents with a given emotion are highly probable to express the same emotion.