At the PITT Computational Social Dynamics Lab (PICSO LAB), we are working toward modeling and analyzing patterns of change within complex social systems, with a focus on patterns of change that emerge from citizen activities, interactions and relationships, and their sensemaking processes.

Our research mission is to use data, big and small, in the service of humanity. Our goal is to empirically study how social systems change and the phenomena of change in society, with behavioral and network data. Our methods include computational approaches such as network analysis and modeling, text mining, and data visualization, as well as qualitative and mixed-methods approaches. Topics of interest include event analytics and modeling, community analysis, self-organizing behaviors in socio-technical systems, and community resilience and sustainability.

The Principal Investigator, Yu-Ru Lin, Associate Professor at the School of Computing and Information, University of Pittsburgh, started this group at 2013. She is a computer scientist by training, with research interests include data science, visualization, and computational social science.

Lab News

  • 2018/02 Paper accepted to appear in ACM TKDD: "Event Analytics via Discriminant Tensor Factorization."
  • 2017/11 Code release -- MTHL (Multi-view Time-Series Hypersphere Learning) for detecting anomalous patterns from dynamic and multi-attributed networks. Check out the github page and our paper!
  • 2017/10 Our studies (about fear & distress) were cited by an article in Las Vegas Sun to explain how the latest mass shooting in Las Vegas could trigger many's lasting emotional reactions regardless of where they live.
  • 2017/09 Congratulations to Xian for receiving travel awards from NSF/SIGWEB/SIGIR to attend CIKM 2017!
  • 2017/05 Congratulations to Xidao Wen for successfully defending his dissertation proposal!
More Updates