Draws, Tim

The JASP guidelines for conducting and reporting a Bayesian analysis

van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., et al. (2021) · Psychonomic Bulletin & Review

Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviews

Cited by 1,114

Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability

Yurrita, M., Draws, T., Balayn, A., Murray-Rust, D., Tintarev, N., & Bozzon, A. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 108

A Checklist to Combat Cognitive Biases in Crowdsourcing

Draws, T., Rieger, A., Inel, O., Gadiraju, U., & Tintarev, N. (2021) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing

Mobile Crowdsensing and CrowdsourcingComputational and Text Analysis Methods

Cited by 86

This Item Might Reinforce Your Opinion: Obfuscation and Labeling of Search Results to Mitigate Confirmation Bias

Rieger, A., Draws, T., Theune, M., & Tintarev, N. (2021) · Proceedings of the 32st ACM Conference on Hypertext and Social Media

Information Retrieval and Search BehaviorInnovative Human-Technology Interaction

Cited by 48

The Effects of Crowd Worker Biases in Fact-Checking Tasks

Draws, T., La Barbera, D., Soprano, M., Roitero, K., Ceolin, D., Checco, A., & Mizzaro, S. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Misinformation and Its ImpactsMobile Crowdsensing and Crowdsourcing

Cited by 23