| More than words: Quantifying language to measure firms' fundamentals PC Tetlock, M SAAR‐TSECHANSKY, S Macskassy The Journal of Finance 63 (3), 1437-1467, 2008 | 3047 | 2008 |
| Classification in networked data: A toolkit and a univariate case study SA Macskassy, F Provost Journal of Machine Learning Research 8 (May), 935-983, 2007 | 718 | 2007 |
| Discovering users' topics of interest on twitter: a first look M Michelson, SA Macskassy Proceedings of the fourth workshop on Analytics for noisy unstructured text …, 2010 | 512 | 2010 |
| A simple relational classifier SA Macskassy, F Provost NEW YORK UNIV NY STERN SCHOOL OF BUSINESS, 2003 | 374 | 2003 |
| Why do people retweet? anti-homophily wins the day! SA Macskassy, M Michelson ICWSM, 209-216, 2011 | 262 | 2011 |
| Confidence bands for ROC curves: Methods and an empirical study S Macskassy, F Provost Proceedings of the First Workshop on ROC Analysis in AI. August 2004., 2004 | 126* | 2004 |
| Confidence Bands for ROC curves S Macskassy, F Provost Stern School of Business, New York University, 2004 | 126 | 2004 |
| ROC confidence bands: an empirical evaluation SA Macskassy, F Provost, S Rosset Proceedings of the 22nd international conference on Machine learning, 537-544, 2005 | 93 | 2005 |
| Human Performance on Clustering Web Pages: A Preliminary Study. SA Macskassy, A Banerjee, BD Davison, H Hirsh KDD, 264-268, 1998 | 92 | 1998 |
| Improving learning in networked data by combining explicit and mined links SA Macskassy PROCEEDINGS OF THE NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE 22 (1), 590, 2007 | 71 | 2007 |
| Using graph-based metrics with empirical risk minimization to speed up active learning on networked data SA Macskassy Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 68 | 2009 |
| Suspicion scoring of networked entities based on guilt-by-association, collective inference, and focused data access1 SA Macskassy, F Provost In Proc. of the First Int. Conf. on Intelligence Analysis (IA), 2005 | 60 | 2005 |
| On the Study of Social Interactions in Twitter. SA Macskassy ICWSM, 2012 | 58 | 2012 |
| Intelligent information triage SA Macskassy, F Provost Proceedings of the 24th annual international ACM SIGIR conference on …, 2001 | 50 | 2001 |
| Joint Inference of Multiple Label Types in Large Networks D Chakrabarti, S Funiak, J Chang, SA Macskassy arXiv preprint arXiv:1401.7709, 2014 | 42 | 2014 |
| Converting numerical classification into text classification SA Macskassy, H Hirsh, A Banerjee, AA Dayanik Artificial Intelligence 143 (1), 51-77, 2003 | 39 | 2003 |
| A brief survey of machine learning methods for classification in networked data and an application to suspicion scoring S Macskassy, F Provost Statistical Network Analysis: Models, Issues, and New Directions, 172-175, 2007 | 38 | 2007 |
| Contextual linking behavior of bloggers: leveraging text mining to enable topic-based analysis SA Macskassy Social Network Analysis and Mining 1 (4), 355-375, 2011 | 22 | 2011 |
| Relational learning problems and simple models F Provost, C Perlich, SA Macskassy Proceedings of the Relational Learning Workshop at IJCAI-2003 11, 2003 | 22 | 2003 |
| Pointwise ROC confidence bounds: An empirical evaluation S Macskassy, F Provost, S Rosset | 21 | 2005 |
Foster ProvostProfessor, New York UniversityVerified email at stern.nyu.edu
