Integrating methods from network analysis, natural language processing, and machine learning with theories from the social sciences to advance knowledge and discovery about interaction-based and communication-based social systems
Jana Diesner

I am an Associate Professor at the School of Information Sciences (the iSchool) at the University of Illinois at Urbana-Champaign, where I lead the Social Computing lab. We focus on Human-Centered Data Science, Social Computing/ Computational Social Science, and Responsible Computing. We integrate and advance methods from network science, natural language processing and machine learning with theories from the social sciences and humanities to study interaction-based and information-based systems. Currently, we are working on projects related to 1) studying consequences of biases in data, technology and human decision making, 2) validating classic social science theories in contemporary settings, 3) impact assessment, 4) crisis informatics, and 5) data governance/ FATE (fairness, accountability, transparency, ethics). I got my PhD from Carnegie Mellon, School of Computer Science.

News from our lab

  • We are excited to have Sul lam Jeoung, Clara Belitz, Angela Rhodes and a group of Undergraduate researchers join the Social Computing Lab! Check our team members from here.
  • Congrats to Ly Dinh being awarded the Grace Hopper Celebration Scholarship.
  • Congrats to Shadi Rezapour being awarded the Bloomberg / NCWIT Conference Grant for Grace Hopper Celebration of Women in Computing.
  • Congrats to Shadi Rezapour being selected to attend and present at the 2nd Annual Michigan Institute for Data Science Consortium for Researchers in Training.
  • Workshop tutorial: Jana, Julian, Janina, and Lan teaching "From Words to Networks: Text-based/ Semantic Network Analysis" at the "Getting Started in Digital Humanities" workshop.
  • New journal paper: Aref, S.*, Dinh, L.*, Rezapour, R.*, & Diesner, J. (2020). Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific Reports 10, 15228. (*Authors contributed equally)
  • New journal paper: Parulian, N., Lu, T., Mishra, S., Avram, M., & Diesner, J. (2020). Effectiveness of the execution and prevention of metric-based adversarial attacks on social network data. Information, 11(6), 306.
  • New workshop paper: Han, K., Yang, P., Mishra, S., & Diesner, J. (2020). WikiCSSH: Extracting Computer Science Subject Headings from Wikipedia. In Proceedings of Scientific Knowledge Graphs Workshop co-located with the 24th International Conference on Theory and Practice of Digital Libraries (TPDL), held online.

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