| Fake news on Twitter during the 2016 U.S. presidential election N Grinberg, K Joseph, L Friedland, B Swire-Thompson, D Lazer Science 363 (6425), 374-378, 2019 | 1724 | 2019 |
| Learning relational probability trees J Neville, D Jensen, L Friedland, M Hay Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge …, 2003 | 312 | 2003 |
| Combating Fake News: An Agenda for Research and Action D Lazer, M Baum, N Grinberg, L Friedland, K Joseph, W Hobbs, ... | 252* | 2017 |
| Auditing Partisan Audience Bias within Google Search RE Robertson, S Jiang, K Joseph, L Friedland, D Lazer, C Wilson Proceedings of the ACM on Human-Computer Interaction 2 (CSCW), 148, 2018 | 208 | 2018 |
| Detecting insider threats in a real corporate database of computer usage activity TE Senator, HG Goldberg, A Memory, WT Young, B Rees, R Pierce, ... Proceedings of the 19th ACM SIGKDD International Conference on Knowledge …, 2013 | 186 | 2013 |
| Exploiting relational structure to understand publication patterns in high-energy physics A McGovern, L Friedland, M Hay, B Gallagher, A Fast, J Neville, D Jensen SIGKDD Explorations 5 (2), 165-172, 2003 | 73 | 2003 |
| Feature Extraction and Machine Learning on Symbolic Music using the music21 Toolkit MS Cuthbert, C Ariza, L Friedland International Society for Music Information Retrieval, 387-392, 2011 | 48 | 2011 |
| Finding tribes: Identifying close-knit individuals from employment patterns L Friedland, D Jensen Proceedings of the 13th ACM SIGKDD International Conference on Knowledge …, 2007 | 46 | 2007 |
| ConStance: Modeling Annotation Contexts to Improve Stance Classification K Joseph, L Friedland, W Hobbs, O Tsur, D Lazer Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 40 | 2017 |
| Relational data pre-processing techniques for improved securities fraud detection A Fast, L Friedland, M Maier, B Taylor, D Jensen, HG Goldberg, ... Proceedings of the 13th ACM SIGKDD International Conference on Knowledge …, 2007 | 34 | 2007 |
| Reshaping a nation: Mobility, commuting, and contact patterns during the COVID-19 outbreak B Klein, T LaRock, S McCabe, L Torres, L Friedland, F Privitera, B Lake, ... Northeastern University-Network Science Institute Report, 2020 | 33 | 2020 |
| Joke retrieval: Recognizing the same joke told differently L Friedland, J Allan Proceedings of the 17th ACM Conference on Information and Knowledge …, 2008 | 22 | 2008 |
| Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Classification L Friedland, A Gentzel, D Jensen Proceedings of the 2014 SIAM International Conference on Data Mining, 578-586, 2014 | 13 | 2014 |
| "Voters of the Year": 19 Voters Who Were Unintentional Election Poll Sensors on Twitter W Hobbs, L Friedland, K Joseph, O Tsur, S Wojcik, D Lazer International AAAI Conference on Web and Social Media, 544-547, 2017 | 8 | 2017 |
| Copy or coincidence? A model for detecting social influence and duplication events L Friedland, D Jensen, M Lavine International Conference on Machine Learning, 1175-1183, 2013 | 7 | 2013 |
| Anomaly Detection for Inferring Social Structure L Friedland Encyclopedia of Data Warehousing and Mining, 39-44, 2009 | 2 | 2009 |
| Detecting Anomalously Similar Entities in Unlabeled Data LD Friedland University of Massachusetts Amherst, 2016 | 1 | 2016 |
| Detecting Social Ties and Copying Events from Affiliation Data L Friedland Fifteenth AAAI/SIGART Doctoral Consortium, 2010 | | 2010 |
David LazerUniversity Distinguished Professor, Northeastern University; & Visiting Scholar, Harvard UniversityVerified email at neu.edu
