Making large-scale support vector machine learning practical
Advances in kernel methods
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Extracting Patterns and Relations from the World Wide Web
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
The Journal of Machine Learning Research
A maximum entropy approach to identifying sentence boundaries
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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)
The relationship between Precision-Recall and ROC curves
ICML '06 Proceedings of the 23rd international conference on Machine learning
Making computers laugh: investigations in automatic humor recognition
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A holistic lexicon-based approach to opinion mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Hunting elusive metaphors using lexical resources
FigLanguages '07 Proceedings of the Workshop on Computational Approaches to Figurative Language
Incorporating domain knowledge into topic modeling via Dirichlet Forest priors
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Keepin' it real: semi-supervised learning with realistic tuning
SemiSupLearn '09 Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing
Hunting for the black swan: risk mining from text
ACLDemos '10 Proceedings of the ACL 2010 System Demonstrations
Wishful thinking: finding suggestions and 'buy' wishes from product reviews
CAAGET '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text
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A wish is "a desire or hope for something to happen." In December 2007, people from around the world offered up their wishes to be printed on confetti and dropped from the sky during the famous New Year's Eve "ball drop" in New York City's Times Square. We present an in-depth analysis of this collection of wishes. We then leverage this unique resource to conduct the first study on building general "wish detectors" for natural language text. Wish detection complements traditional sentiment analysis and is valuable for collecting business intelligence and insights into the world's wants and desires. We demonstrate the wish detectors' effectiveness on domains as diverse as consumer product reviews and online political discussions.