University Of Michigan: Research Institution — Prolific Citations Library

Browse 10 peer-reviewed papers from University Of Michigan spanning Human-Computer Interaction (HCI), Social Media (2021–2026). Research powered by Prolific's high-quality participant data.

This page lists 10 peer-reviewed papers from researchers at University Of Michigan in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (10 of 10)

The Artificial Intelligence Disclosure Penalty: Humans Persistently Devalue AI-Generated Creative Writing

Authors: M Raj, JM Berg, R Seamans

Year: 2026

Published in: Journal of Experimental Psychology …, 2026 - psycnet.apa.org

Institution: New York University, University of Michigan, Wharton

Research Area: Disclosure psychology, Biases in human–machine evaluation, AI Biases

Discipline: Experimental psychology

This paper sits at the intersection of experimental psychology, social cognition, and consumer judgment, examining how AI disclosure triggers persistent authenticity-based bias against creative work, revealing a robust form of algorithmic aversion in symbolic and expressive domains.

DOI: https://doi.org/10.1037/xge0001889
The Impact of Generative AI on Social Media: An Experimental Study

Authors: AG Møller, DM Romero, D Jurgens

Year: 2025

Published in: arXiv preprint arXiv ..., 2025 - arxiv.org

Institution: University of Copenhagen, University of Michigan, Pioneer Centre for AI

Research Area: Generative AI, Social Media, Human-Computer Interaction (HCI)

Discipline: Computational Social Science

Generative AI tools on social media increase user engagement and content volume but reduce perceived quality and authenticity in discussions, highlighting challenges for ethical integration.

Methods: Controlled experiment with participants assigned to small discussion groups under distinct AI-assisted treatment conditions including chat assistance, conversation starters, feedback on comment drafts, and reply suggestions.

Key Findings: Impact of generative AI tools on user behavior, engagement, content volume, perceived quality, and authenticity in social media interactions.

DOI: https://doi.org/10.48550/arXiv.2506.14295

Citations: 9

Sample Size: 680
Blissful (A)Ignorance: People form overly positive impressions of others based on their written messages, despite wide-scale adoption of Generative AI

Authors: Jiaqi Zhua, Andras Molnar

Year: 2025

Published in: ArXiv

Institution: University of Michigan

Research Area: Social Psychology, Human-AI Interaction, Generative AI Impact on Social Perception

Discipline: Social Science, Social Psychology, Human-Computer Interaction (HCI)

Impressions of written messages are overly positive when recipients are unaware of potential Generative AI (GenAI) use, but negative when GenAI use is explicitly disclosed.

Methods: A pre-registered large-scale online experiment leveraged Prolific participants to assess social impressions in diverse communication contexts, with varying levels of sender disclosure regarding GenAI use.

Key Findings: The influence of known or uncertain GenAI use on recipients' social impressions of message senders across different personal and professional contexts.

Sample Size: 647
I know this looks bad, but I can explain: Understanding when AI should explain actions in human-AI teams

Authors: R Zhang, C Flathmann, G Musick, B Schelble

Year: 2024

Published in: ACM Transactions on ..., 2024 - dl.acm.org

Institution: North Carolina State University, University of North Carolina at Charlotte, University of Georgia, University of Michigan

Research Area: Explainable AI (XAI), Human-AI Teaming, Human-Computer Interaction (HCI)

Discipline: Robotics, Artificial Intelligence

Explored how AI explanations impact human trust and team effectiveness in human-AI teams, finding that explanations increase trust when AI disobeys orders but reduce trust when AI lies, with individual characteristics influencing these perceptions.

Methods: Conducted an online experiment analyzing participant responses to scenarios where AI explained its actions within a teamwork context, comparing trust in AI versus human teammates.

Key Findings: Impact of AI explanations on human trust, team effectiveness, and how these vary with teammate identity (human or AI) and participant characteristics (e.g., gender, ethical framework).

DOI: https://doi.org/10.1145/3635474

Citations: 28

Sample Size: 156
Empowering social media users: nudge toward self-engaged verification for improved truth and sharing discernment

Authors: F Tu

Year: 2024

Published in: Journal of Communication, 2024 - academic.oup.com

Institution: University of Michigan

Research Area: Social Media, Misinformation, Self-Verification, User Empowerment

Discipline: Communication Studies

DOI: https://doi.org/10.1093/joc/jqae007

Citations: 8
Family Stress Processes Underlying COVID-19–Related Economic Insecurity for Mothers and Fathers and Children's Internalizing Behaviour Problems

Authors: Joyce Y. Lee, Shawna J. Lee, Sehun Oh, Amy Xu, Angelise Radney, Christina M. Rodriguez

Year: 2024

Published in: Wiley

Institution: Old Dominion University, The Ohio State University, University of Michigan

Research Area: Family Stress Model, Child Psychology

Discipline: Social Science
Learning to prioritize the public good: Does training in classes, workplaces, and professional societies shape engineers' understanding of their public welfare responsibilities?

Authors: Erin A. Cech, Cynthia J. Finelli

Year: 2024

Published in: Wiley

Institution: University of Michigan

Research Area: Engineering Ethics, Professional Responsibility, Public Welfare

Discipline: Engineering Education Research
When do annotator demographics matter? measuring the influence of annotator demographics with the POPQUORN dataset

Authors: J Pei, D Jurgens

Year: 2023

Published in: arXiv preprint arXiv:2306.06826, 2023 - arxiv.org

Institution: University of Michigan, University of Toronto

Research Area: Natural Language Processing (NLP)

Discipline: Natural Language Processing, Human-Computer Interaction (HCI)

DOI: https://doi.org/10.48550/arXiv.2306.06826

Citations: 55
Are privacy dashboards good for end users? Evaluating user perceptions and reactions to Google's My Activity

Authors: FM Farke, DG Balash, M Golla, M Dürmuth

Year: 2021

Published in: 30th USENIX Security ..., 2021 - usenix.org

Institution: Ruhr University Bochum, Max Planck Institute, University of Michigan, CISPA Helmholtz Center for Information Security

Research Area: Human-Computer Interaction (HCI), Privacy, User Security

Discipline: Human-Computer Interaction (HCI), Privacy, Security in Computer Science, Social Science Research.

Citations: 80
Are we all in this together?": Brand opportunism in covid-19 cause related marketing and the moderating role of consumer skepticism

Authors: J Yang, J Mundel

Year: 2021

Published in: Journal of Promotion Management, 2021 - Taylor & Francis

Institution: Michigan State University

Research Area: Cause-related Marketing, Consumer Skepticism, Consumer Attitude

Discipline: Marketing

DOI: https://doi.org/10.1080/10496491.2021.1888181

Citations: 37