| Matching organizational structure and social network extracted from email communication R Michalski, S Palus, P Kazienko Business Information Systems: 14th International Conference, BIS 2011 …, 2011 | 177 | 2011 |
| Seed selection for spread of influence in social networks: Temporal vs. static approach R Michalski, T Kajdanowicz, P Bródka, P Kazienko New Generation Computing 32, 213-235, 2014 | 55 | 2014 |
| Combining machine learning and social network analysis to reveal the organizational structures M Nurek, R Michalski Applied Sciences 10 (5), 1699, 2020 | 49 | 2020 |
| Balancing speed and coverage by sequential seeding in complex networks J Jankowski, P Bródka, P Kazienko, BK Szymanski, R Michalski, ... Scientific reports 7 (1), 891, 2017 | 49 | 2017 |
| Knowledge workers’ collaborative learning behavior modeling in an organizational social network P Różewski, J Jankowski, P Brodka, R Michalski Computers in Human Behavior 51, 1248-1260, 2015 | 48 | 2015 |
| CasSeqGCN: Combining network structure and temporal sequence to predict information cascades Y Wang, X Wang, Y Ran, R Michalski, T Jia Expert Systems with Applications 206, 117693, 2022 | 47 | 2022 |
| Revealing the character of nodes in a blockchain with supervised learning R Michalski, D Dziubałtowska, P Macek Ieee Access 8, 109639-109647, 2020 | 40 | 2020 |
| eSource for clinical trials: implementation and evaluation of a standards-based approach in a real world trial JF Ethier, V Curcin, MM McGilchrist, SNLC Keung, L Zhao, A Andreasson, ... International Journal of Medical Informatics 106, 17-24, 2017 | 32 | 2017 |
| Finding influentials in social networks using evolutionary algorithm M Weskida, R Michalski Journal of Computational Science 31, 77-85, 2019 | 31 | 2019 |
| Entropy measures of human communication dynamics M Kulisiewicz, P Kazienko, BK Szymanski, R Michalski Scientific reports 8 (1), 15697, 2018 | 27 | 2018 |
| Predicting Social Network Measures using Machine Learning Approach R Michalski, P Kazienko, D Król Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM …, 2012 | 27 | 2012 |
| Evolutionary algorithm for seed selection in social influence process M Weskida, R Michalski 2016 IEEE/ACM International Conference on Advances in Social Networks …, 2016 | 25 | 2016 |
| Probing limits of information spread with sequential seeding J Jankowski, BK Szymanski, P Kazienko, R Michalski, P Bródka Scientific reports 8 (1), 1-9, 2018 | 24 | 2018 |
| Compensatory seeding in networks with varying avaliability of nodes J Jankowski, R Michalski, P Kazienko Proceedings of the 2013 IEEE/ACM International Conference on Advances in …, 2013 | 24 | 2013 |
| The multidimensional study of viral campaigns as branching processes J Jankowski, R Michalski, P Kazienko Social Informatics: 4th International Conference, SocInfo 2012, Lausanne …, 2012 | 23 | 2012 |
| A multilayer network dataset of interaction and influence spreading in a virtual world J Jankowski, R Michalski, P Bródka Scientific data 4 (1), 1-9, 2017 | 22 | 2017 |
| Social network analysis as a tool for improving enterprise architecture P Kazienko, R Michalski, S Palus KES International Symposium on Agent and Multi-Agent Systems: Technologies …, 2011 | 19 | 2011 |
| Maximizing social influence in real-world networks—the state of the art and current challenges R Michalski, P Kazienko Propagation Phenomena in Real World Networks, 329-359, 2015 | 17 | 2015 |
| Effective influence spreading in temporal networks with sequential seeding R Michalski, J Jankowski, P Bródka IEEE Access 8, 151208-151218, 2020 | 15 | 2020 |
| Negative effects of incentivised viral campaigns for activity in social networks R Michalski, J Jankowski, P Kazienko 2012 Second International Conference on Cloud and Green Computing, 391-398, 2012 | 15 | 2012 |
Przemysław KazienkoPolitechnika WrocławskaVerified email at pwr.edu.pl
