Tae Yano
Cited by
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Predicting response to political blog posts with topic models
T Yano, WW Cohen, NA Smith
Proceedings of Human Language Technologies: The 2009 Annual Conference of …, 2009
What’s worthy of comment? content and comment volume in political blogs
T Yano, N Smith
Proceedings of the International AAAI Conference on Web and Social Media 4 (1), 2010
Textual predictors of bill survival in congressional committees
T Yano, NA Smith, JD Wilkerson
Proceedings of the 2012 Conference of the North American Chapter of the …, 2012
Shedding (a thousand points of) light on biased language
T Yano, P Resnik, NA Smith
Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language …, 2010
Seeing a home away from the home: Distilling proto-neighborhoods from incidental data with Latent Topic Modeling
J Cranshaw, T Yano
CSSWC Workshop at NIPS 10, 2010
Identifying salient entities in web pages
M Gamon, T Yano, X Song, J Apacible, P Pantel
Proceedings of the 22nd ACM international conference on Information …, 2013
Exploring venue-based city-to-city similarity measures
D Preoţiuc-Pietro, J Cranshaw, T Yano
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing, 1-4, 2013
A penny for your tweets: Campaign contributions and capitol hill microblogs
T Yano, D Yogatama, N Smith
Proceedings of the International AAAI Conference on Web and Social Media 7 (1), 2013
Relation between agreement measures on human labeling and machine learning performance: Results from an art history image indexing domain
RJ Passonneau, T Yano, T Lippincott, J Klavans
Computational Linguistics for Metadata Building 49, 2008
Taking advantage of wikipedia in natural language processing
T Yano, M Kang
Technical report, Carnegie Mellon University Language Technologies Institute, 2016
Understanding document aboutness step one: Identifying salient entities
M Gamon, T Yano, X Song, J Apacible, P Pantel
Microsoft Research, 2013
Identifying salient items in documents
M Gamon, P Pantel, X Song, T Yano, JT Apacible
US Patent 9,251,473, 2016
Social and affective responses to political information
D Pierce, DP Redlawsk, WW Cohen, T Yano, R Balasubramanyan
American Political Science Association Annual Meeting, New Orleans, Louisiana, 2012
Structured databases of named entities from Bayesian nonparametrics
J Eisenstein, T Yano, WW Cohen, NA Smith, EP Xing
Proceedings of the First Workshop on Unsupervised Learning in NLP, 2-12, 2011
Functional semantic categories for art history text: human labeling and preliminary machine learning
R Passonneau, T Yano, T Lippincott, J Klavans
International Conference on Computer Vision Theory and Applications …, 2008
Computational linguistics for metadata building: Aggregating text processing technologies for enhanced image access
J Klavans, C Sheffield, E Abels, J Beaudoin, L Jenemann, T Lipincott, ...
Proc. of the Language Resources for Content-Based Image Retrieval Workshop …, 2008
Text as Actuator: Text-Driven Response Modeling and Prediction in Politics
T Yano
Carnegie Mellon University, 2013
Assessing the effects of emotion-laden messages in a social network
D Redlawsk, D Pierce, W Cohen, T Yano, R Balasubramanyan
APSA 2011 Annual Meeting Paper, 2011
Experiments on Non-Topical Paragraph Classification of the Art History Textbook
T Yano
unpublished, 2007
Understanding Document Aboutness Step One: Identifying Salient Entities
PP Michael Gamon, Tae Yano, Xinying Song, Johnson
Microsoft Technical Report (MSR-TR-2013-73), 2013
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