Emotions from text: machine learning for text-based emotion prediction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Emotion Classification Using Web Blog Corpora
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Building emotion lexicon from weblog corpora
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
SemEval-2007 task 14: affective text
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Analysis and tracking of emotions in english and bengali texts: a computational approach
Proceedings of the 20th international conference companion on World wide web
Sentence to document level emotion tagging - a coarse-grained study on Bengali Blogs
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
An affect-enriched dialogue act classification model for task-oriented dialogue
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Finding emotion in image descriptions
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Emotion tracking on blogs - a case study for bengali
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Set-Similarity joins based semi-supervised sentiment analysis
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Joint learning on sentiment and emotion classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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In this paper, emotion analysis on blog texts has been carried out for a less privileged language like Bengali. Ekman's six basic emotion types have been selected for reliable and semi automatic word level annotation. An automatic classifier has been applied for recognizing six basic emotion types for different words in a sentence. Application of different scoring strategies to identify sentence level emotion tag based on the acquired word level emotion constituents have produced satisfactory performance.