| A survey on bias and fairness in machine learning N Mehrabi, F Morstatter, N Saxena, K Lerman, A Galstyan ACM computing surveys (CSUR) 54 (6), 1-35, 2021 | 5612 | 2021 |
| Information contagion: An empirical study of the spread of news on digg and twitter social networks K Lerman, R Ghosh Proceedings of the international AAAI conference on web and social media 4 …, 2010 | 1287 | 2010 |
| Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing S Abu-El-Haija, B Perozzi, A Kapoor, N Alipourfard, K Lerman, ... international conference on machine learning, 21-29, 2019 | 1082 | 2019 |
| Tracking social media discourse about the covid-19 pandemic: Development of a public coronavirus twitter data set E Chen, K Lerman, E Ferrara JMIR public health and surveillance 6 (2), e19273, 2020 | 845 | 2020 |
| The DARPA Twitter bot challenge VS Subrahmanian, A Azaria, S Durst, V Kagan, A Galstyan, K Lerman, ... Computer 49 (6), 38-46, 2016 | 583 | 2016 |
| Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign A Badawy, E Ferrara, K Lerman Proceedings of The international conference series on Advances in Social …, 2018 | 493 | 2018 |
| Social information processing in news aggregation K Lerman IEEE internet computing 11 (6), 16-28, 2007 | 471 | 2007 |
| Using a model of social dynamics to predict popularity of news K Lerman, T Hogg Proceedings of the 19th international conference on World wide web, 621-630, 2010 | 418 | 2010 |
| Analysis of dynamic task allocation in multi-robot systems K Lerman, C Jones, A Galstyan, MJ Matarić The International Journal of Robotics Research 25 (3), 225-241, 2006 | 375 | 2006 |
| Distributed online localization in sensor networks using a moving target A Galstyan, B Krishnamachari, K Lerman, S Pattem Proceedings of the 3rd international symposium on Information processing in …, 2004 | 374 | 2004 |
| The simple rules of social contagion NO Hodas, K Lerman Scientific reports 4 (1), 4343, 2014 | 364 | 2014 |
| Semi-automatically mapping structured sources into the semantic web CA Knoblock, P Szekely, JL Ambite, A Goel, S Gupta, K Lerman, ... Extended semantic web conference, 375-390, 2012 | 317 | 2012 |
| The" majority illusion" in social networks K Lerman, X Yan, XZ Wu PloS one 11 (2), e0147617, 2016 | 304 | 2016 |
| Mathematical model of foraging in a group of robots: Effect of interference K Lerman, A Galstyan Autonomous robots 13, 127-141, 2002 | 304 | 2002 |
| Wrapper maintenance: A machine learning approach K Lerman, SN Minton, CA Knoblock Journal of Artificial Intelligence Research 18, 149-181, 2003 | 263 | 2003 |
| Social browsing on flickr K Lerman, L Jones International Conference of Weblogs and Social Media (ICWSM 2006), 2006 | 262 | 2006 |
| Accurately and reliably extracting data from the web: A machine learning approach CA Knoblock, K Lerman, S Minton, I Muslea Intelligent exploration of the web, 275-287, 2003 | 252 | 2003 |
| A review of probabilistic macroscopic models for swarm robotic systems K Lerman, A Martinoli, A Galstyan Swarm Robotics: SAB 2004 International Workshop, Santa Monica, CA, USA, July …, 2005 | 235 | 2005 |
| Political polarization drives online conversations about COVID‐19 in the United States J Jiang, E Chen, S Yan, K Lerman, E Ferrara Human Behavior and Emerging Technologies 2 (3), 200-211, 2020 | 234 | 2020 |
| Using the structure of web sites for automatic segmentation of tables K Lerman, L Getoor, S Minton, C Knoblock Proceedings of the 2004 ACM SIGMOD international conference on Management of …, 2004 | 219 | 2004 |
Emilio FerraraProfessor of Computer Science at the University of Southern CaliforniaEmail verificata su usc.edu