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Welcome to the Social Intelligence Lab

Welcome to the Social Intelligence Lab

Welcome to the Social Intelligence Lab

Social Information Technologies for a Better World

The Social Intelligence Lab at Bar-Ilan University is dedicated to leading edge research on social uses of information and communication technologies, the underlying nature of socially generated data, and algorithms that use both social data and network effects to improve society.  Our work is both theoretical and applied, qualitative and quantitative, seeking to translate new understanding of the nature of technology-based social interactions into system designs and applications. Established by Prof. David Schwartz of the Graduate School of Business Administration, SOCINTLAB currently houses research projects focused on digital therapeutics, medical informatics, information security in social networks, human-in-the-loop AI, and how social networks and media change critical interactions of individuals, organizations, and societies.

Research Areas and Projects

UnityPhilly: Opioid Overdose ERC

Reciprocal Human-Machine Learning (RHML)

Emergency Response Communities

Medical Informatics, mHealth and Digital Therapeutics (DTx)

FUSION - the 1st RHML Implementation

Online Discourse, Censorship and Information Security

Social CRM

Recent Publications

Cohen, D., Te’eni, D., Yahav, I., Zagalsky, A., Schwartz, D., Silverman, G., Mann, Y., Elalouf, A., & Makowski, J. (2025). Human–AI Enhancement of Cyber Threat Intelligence. International Journal of Information Security, 24(2), Article 99. https://doi.org/10.1007/s10207-025-01004-4
Sha, Y., Roth, A., Lankenau, S., Schwartz, D. G., & Marcu, G. (2025). Meeting People Where They Are: Building Community-Centered Care with Smartphone-Facilitated Response to Overdoses. Proceedings of the ACM on Human-Computer Interaction, 9(1), Article GROUP21. https://doi.org/10.1145/3701200
Rioux, W., Viste, D., Sedaghat, N., Rider, N., Tek, J. T. W., Perri, M., Schwartz, D. G., Ritchie, K., Carrà, G., Carreiro, S., Kreig, O., Marcu, G., Arthur, J., Cogdell, J., Brown, M., Marshall, T., & Ghosh, S. M. (2025). Defining terminology and outcome measures for evaluating overdose response technology: An international Delphi study. Drug and Alcohol Review, 44(5), 1430-1443. https://doi.org/10.1111/dar.14055
Silverman, G., Te’eni, D., Schwartz, D. G., Mann, Y., Cohen, D., & Lewinsky, D. (Accepted/In press). A hybrid mixed methods design of qualitative enhancement and reciprocal feedback loop for augmented text classification. Quality and Quantity. https://doi.org/10.1007/s11135-025-02108-8

Introducing UnityPhilly and Emergency Response Communities

Introducing UnityPhilly and Emergency Response Communities

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