Young Anna Argyris Ph.D.

Young Argyris

Associate Professor

Department
  • Media & Information
argyris@msu.edu
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Bio

Young Anna Argyris is an Associate Professor in the Department of Media and Information at Michigan State University. She has received a Ph.D. in Management Information Systems from the Sauder School of Business, University of British Columbia, Canada.


Previous Experience

Before joining MSU, she was an assistant professor at the Gabelli School of Business, Fordham University, and a visiting scholar at Carroll School of Management, Boston College.

Research Areas

Dr. Argyris’s research centers on the design, development, and use of Information Technology to aid users’ decision-making and create social influence. Her application areas center on health misinformation and social media influencers. With her collaborators in Computer Science, Dr. Argyris has developed deep learning models for classifying vaccine misinformation propagated on social media that hampers Human-papilloma virus vaccine uptakes among US teens. In addition, Dr. Argyris has applied deep learning models to identify how “visual congruence” (the similarity portrayed in visual elements of social media posts between message sources and recipients) can augment the sources’ influences on the receivers. From these studies, Dr. Argyris has proposed a new concept, visual congruence-induced social influence, which she uses to create influential social media campaigns to counteract health misinformation.

Academic Contributions

Her previous work has appeared in MIS QuarterlyInformation Systems ResearchCommunication of the ACMACM Transactions on Computer-Human InteractionJournal of Information Technology, and International Journal of Electronic Commerce, among others.

Social Contributions

She is an active contributor to the Information Systems community. She serves as an associate editor for many conferences, including International Conferences on Information Systems, and as an ad-hoc reviewer for renowned journals such as MIS Quarterly and Information Systems Research.

Dr. Argyris is the principal investigator of an R21 grant from the National Library of Medicine, National Institutes of Health, on the project entitled Development of a vaccine misinformation portal and its application to identifying the impact of social media vaccine posts on immunization rates during a global pandemic. Dr. Argyris is also a co-PI of the National Science Foundation, Future of Work program on team collaboration. 

 


Latest Publications:
  1. * Nelson, V.‡, Bashyal, B., Tan, P. & Argyris, Y. (2024) “Vaccine rhetoric on social media and COVID-19 vaccine uptake rates: A triangulation using self-reported vaccine acceptance,” (in press) Social Science and Medicine, IF = 5.379 (Q1, 30/182, SSCI: Public, environmental & occupational health)
  2. Ruggeri, K., Vanderslott, S., Yamada, Y., Argyris, Y., Veckalov, B., Boggio, P., Fallah, M., Stock, F., & Hertwig, R., (2024) "Improving behavioral interventions to reduce vaccine hesitancy: The evidence we have is not enough," the British Medical Journal, Impact Factor (IF) = 107.7 (Q1, SCIE: 4/169 Medical, general & internal)
  3. * Argyris, Y., Nelson, V., Wiseley, K., Shen, R., and Roscizewski, A. (2022) “Do Social Media Campaigns Foster Vaccination Adherence? A Systematic Review of Prior Intervention-Based Campaigns on Social Media,” Telematics and Informatics, 101918, https://doi.org/10.1016/j.tele.2022.101918, impact factor = 9.140, (Q1, SSCI: 4/84 information Science & library science).
  4. * Argyris, Y., Kim, Y., Roscizewski, A., and Song, W. (2021) “The Mediating Role of Vaccine Hesitancy between Maternal Engagement with Anti- and Pro-vaccine Social Media Posts and Adolescent HPV-Vaccine Uptake Rates in the US: The Perspective of Loss Aversion in Emotion-Laden Decision Circumstances,” Social Science and Medicine (1982), 282, 114043. https://doi.org/10.1016/j.socscimed.2021.114043, impact factor (IF) = 5.379 (Q1, 30/182, SSCI: Public, environmental & occupational health)
  5. * Argyris, Y., Monu, K., Tan, P-N., Aarts, C., Jing, F. and Wisely, K.  (2021) “Using Machine Learning to Compare Provaccine and Antivaccine Discourse Among the Public on Social Media: Algorithm Development Study,” JMIR Public Health and Surveillance, 7(6), e23105. https://doi.org/10.2196/23105, IF = 14.557 (Q1, 5/182, SSCI: Public, environmental & occupational health

* denotes publications with student co-authors. ‡ denotes graduate students. All the journal publications are peer-reviewed.

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Contact Information

404 Wilson Rd.
Communication Arts and Sciences Building
Michigan State University