Maria Molina

Assistant Professor of Advertising and Public Relations Michigan State University

  • East Lansing MI

Maria Molina's research explores the social and psychological implications of sharing online.

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Michigan State University

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Biography

Maria D. Molina is an Assistant Professor in the Department of Advertising & Public Relations. She received her PhD in Mass Communications from Penn State University.

Maria studies online persuasion in the context of digital health, fake news, and online privacy using a combination of experimental and computational approaches. Her research explores the social and psychological implications of sharing online, focusing on how technology shapes what we share on social media, and how we respond to artificial intelligence tools that curate user-generated content.

Industry Expertise

Education/Learning

Areas of Expertise

Sharing Online
Social Media
AI-Human Interaction
Psychology of Human-Computer Interaction
Media Effects
Digital Health
Fake News

Accomplishments

AEJMC News Audience Research Paper Award, Association for Education in Journalism and Mass Communication

2019

Third Place Student Research Competition, CHI Conference on Human Factors in Computing Systems.

2019

Excellence in Communications Doctoral Award, Dr. Marie Hardin and Mr. Jerry Kammer

2019

Education

Pennsylvania State University

Ph.D.

Mass Communications

2020

New Mexico State University

M.A.

Communication Studies

2014

West Texas A&M University

B.A.

Mass Communications-Broadcasting and Speech Communication

2012

Affiliations

  • Association for Computing Machinery (ACM)
  • ACM Special Interest Group on Computer-Human Interaction (SIGCHI)
  • International Communication Association (ICA)

Event Appearances

Can fitness applications increase physical activity? a novel application of propensity score matching in testing the effects of technological affordances on self-reported physical activity change?

72nd annual conference of the International Communication Association (ICA)  

Moderating harmful online content: Can collaboration between AI and humans enhance trust and acceptance of content classification systems?

71th annual conference of the International Communication Association (ICA)  

Seeing is believing: Is video modality more powerful in spreading Fake News via online messaging apps?

103rd annual conference of the Association for Education in Journalism and Mass Communication (AEJMC)  San Francisco, CA

Journal Articles

One AI Does Not Fit All: A Cluster Analysis of the Laypeople’s Perception of AI Roles

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

2023

Artificial intelligence (AI) applications have become an integral part of our society. However, studying AI as one entity or studying idiosyncratic applications separately both have limitations. Thus, this study used computational methods to categorize ten different AI roles prevalent in our everyday life and compared laypeople’s perceptions of them using online survey data (N = 727).

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Motivation to Use Fitness Application for Improving Physical Activity Among Hispanic Users: The Pivotal Role of Interactivity and Relatedness

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

2023

Is the current state of fitness applications effective at motivating and satisfying the needs of Hispanic users? With most mHealth research conducted with a predominantly white population, the answer to this question is lacking. In this study, we address this question through a survey study with Hispanic users of fitness applications (N= 211) and use the Motivational Technology Model (MTM) and Self-Determination Theory (SDT) as theoretical frameworks.

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Do people believe in misleading information disseminated via memes? The role of identity and anger

New Media & Society

2023

Do people believe in misleading information disseminated via contemporary Internet memes? Do they believe in it more compared with information provided via text? This research explores these questions via a 3 (modality: contemporary internet meme vs text-only vs text-with-explanation) × 2 (identity-congruence: congruent vs incongruent) between-subject online experiment, using two contexts of investigation (crime and taxes).

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