Suri, Siddharth
Microsoft (United States) · Microsoft Research New York City (United States)
8 papers on CoChatORCID 0000-0002-1318-8140
Most cited papers
- Verified
Conducting behavioral research on Amazon’s Mechanical Turk
Mason, W., & Suri, S. (2012) · Behavior Research Methods
Mobile Crowdsensing and CrowdsourcingExperimental Behavioral Economics Studies
Cited by 3,172
- Verified
The effects of remote work on collaboration among information workers
Yang, L., Holtz, D., Jaffe, S., Suri, S., Sinha, S., Weston, J., Joyce, C., Shah, N., Sherman, K., Hecht, B., et al. (2021) · Nature Human Behaviour
Work-Family Balance ChallengesTeam Dynamics and Performance
Cited by 789
- Verified
The impact of generative artificial intelligence on socioeconomic inequalities and policy making
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., et al. (2024) · PNAS Nexus
Ethics and Social Impacts of AITechnology's Impact on Media
Cited by 371
- Verified
Cooperation and assortativity with dynamic partner updating
Wang, J., Suri, S., & Watts, D. J. (2012) · Proceedings of the National Academy of Sciences
Evolutionary Game Theory and CooperationExperimental Behavioral Economics Studies
Cited by 198
- Verified
The economic and cognitive costs of annoying display advertisements
Goldstein, D. G., Suri, S., McAfee, R. P., Ekstrand-Abueg, M., & Diaz, F. (2014) · Journal of Marketing Research
Digital Marketing and Social MediaConsumer Market Behavior and Pricing
Cited by 151
- Verified
Incentivizing High Quality Crowdwork
Ho, C.-J., Slivkins, A., Suri, S., & Vaughan, J. W. (2015) · Proceedings of the 24th International Conference on World Wide Web
Mobile Crowdsensing and CrowdsourcingExperimental Behavioral Economics Studies
Cited by 146
- Verified
Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies
Shah, C., White, R. W., Andersen, R., Buscher, G., Counts, S., Das, S. S. S., Montazer, A., Manivannan, S., Neville, J., Ni, X., et al. (2023) · arXiv
Information Retrieval and Search BehaviorRecommender Systems and Techniques
Cited by 33
- Verified
Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies
Shah, C., White, R., Andersen, R., Buscher, G., Counts, S., Das, S., Montazer, A., Manivannan, S., Neville, J., Rangan, N., et al. (2025) · ACM Transactions on the Web
Information Retrieval and Search BehaviorRecommender Systems and Techniques
Cited by 33
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