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 | 143 | 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 | 136 | 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 | 98 | 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 | 95 | 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 | 50 | 2013 |
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 | 49 | 2010 |
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 | 46 | 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 | 19 | 2013 |
Taking advantage of wikipedia in natural language processing T Yano, M Kang Technical report, Carnegie Mellon University Language Technologies Institute, 2016 | 17 | 2016 |
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 | 16 | 2008 |
Identifying salient items in documents M Gamon, P Pantel, X Song, T Yano, JT Apacible US Patent 9,251,473, 2016 | 13 | 2016 |
Understanding document aboutness step one: Identifying salient entities M Gamon, T Yano, X Song, J Apacible, P Pantel Microsoft Research, 2013 | 13 | 2013 |
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 | 10 | 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 | 8 | 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 | 8 | 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 | 3 | 2008 |
Text as Actuator: Text-Driven Response Modeling and Prediction in Politics T Yano Carnegie Mellon University, 2013 | 1 | 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 | 1 | 2011 |
Experiments on Non-Topical Paragraph Classification of the Art History Textbook T Yano unpublished, 2007 | 1 | 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 | | 2013 |