Haiyi Zhu

Kraut, R. E., Li, H. ., & Zhu, H. . (2022). Mental health during the COVID-19 pandemic: Impacts of disease, social isolation, and financial stressors. PLOS ONE, 17(11), 1. http://doi.org/10.1371/journal.pone.0277562

Sun, L. ., Liu, Y. ., Joseph, G. ., Yu, Z. ., Zhu, H. ., & Dow, S. P. (2022). Comparing Experts and Novices for AI Data Work: Insights on Allocating Human Intelligence to Design a Conversational Agent. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 10(1), 12. http://doi.org/10.1609/hcomp.v10i1.21999

Fang, A. ., & Zhu, H. . (2022). Matching for Peer Support: Exploring Algorithmic Matching for Online Mental Health Communities. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 37. http://doi.org/10.1145/3555202

Yao, Z. ., Zhu, H. ., & Kraut, R. E. (2022). Learning to Become a Volunteer Counselor: Lessons from a Peer-to-Peer Mental Health Community. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 24. http://doi.org/10.1145/3555200

Coston, A. ., Kawakami, A. ., Zhu, H. ., Holstein, K. ., & Heidari, H. . (2023). A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms. In (p. 15). IEEE. http://doi.org/10.1109/SaTML54575.2023.00050

Fang, A. ., & Zhu, H. . (2023). Measuring the Stigmatizing Effects of a Highly Publicized Event on Online Mental Health Discourse. In (p. 18). ACM. http://doi.org/10.1145/3544548.3581284

Kuo, T.-S. ., Shen, H. ., Geum, J. ., Jones, N. ., Hong, J. I., Zhu, H. ., & Holstein, K. . (2023). Understanding Frontline Workers’ and Unhoused Individuals’ Perspectives on AI Used in Homeless Services. In (p. 17). ACM. http://doi.org/10.1145/3544548.3580882

Hsieh, J. ., Adisa, O. ., Bafna, S. ., & Zhu, H. . (2023). Designing Individualized Policy and Technology Interventions to Improve Gig Work Conditions. In (p. 9). ACM. http://doi.org/10.1145/3596671.3598576

Hsieh, J. ., Karger, M. ., Zagal, L. ., & Zhu, H. . (2023). Co-Designing Alternatives for the Future of Gig Worker Well-Being: Navigating Multi-Stakeholder Incentives and Preferences. In (p. 24). ACM. http://doi.org/10.1145/3563657.3595982

Hsieh, J. ., Kim, J. ., Dabbish, L. ., & Zhu, H. . (2023). "Nip it in the Bud": Moderation Strategies in Open Source Software Projects and the Role of Bots. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW2), 29. http://doi.org/10.1145/3610092