Argyle, Lisa P.

Exposure to opposing views on social media can increase political polarization

Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. B. F., Lee, J., Mann, M., Merhout, F., & Volfovsky, A. (2018) · Proceedings of the National Academy of Sciences

Social Media and PoliticsMedia Influence and Politics

Cited by 1,863

Out of One, Many: Using Language Models to Simulate Human Samples

Argyle, L. P., Busby, E. C., Fulda, N., Gubler, J. R., Rytting, C., & Wingate, D. (2023) · Political Analysis

Ethics and Social Impacts of AIComputational and Text Analysis Methods

Cited by 783

Measuring the predictability of life outcomes with a scientific mass collaboration

Salganik, M. J., Lundberg, I., Kindel, A. T., Ahearn, C. E., Al-Ghoneim, K., Almaatouq, A., Altschul, D. M., Brand, J. E., Carnegie, N. B., Compton, R. J., et al. (2020) · Proceedings of the National Academy of Sciences

Family Dynamics and RelationshipsOnline Learning and Analytics

Cited by 322

Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale

Argyle, L. P., Bail, C. A., Busby, E. C., Gubler, J. R., Howe, T., Rytting, C., Sorensen, T., & Wingate, D. (2023) · Proceedings of the National Academy of Sciences

Social Media and PoliticsMisinformation and Its Impacts

Cited by 144

Testing theories of political persuasion using AI

Argyle, L. P., Busby, E. C., Gubler, J. R., Lyman, A., Olcott, J., Pond, J., & Wingate, D. (2025) · Proceedings of the National Academy of Sciences

Electoral Systems and Political ParticipationOpinion Dynamics and Social Influence

Cited by 53

Towards Coding Social Science Datasets with Language Models

Rytting, C. M., Sorensen, T., Argyle, L., Busby, E., Fulda, N., Gubler, J., & Wingate, D. (2023) · arXiv

Computational and Text Analysis MethodsArtificial Intelligence in Law

Cited by 18