Faculty Feature of the Month

November 6, 2020 - Jade Greear

Our November Faculty Feature of the Month is Dr. Young Anna Argyris. A professor in the Department of Media and Information since 2014, Dr. Argyris’s research focuses on the use of social media to facilitate individual and collective decision-making processes through creating the viral dissemination of content to and exerting social influence on the audiences. Most recently, this work has centered on visual congruence-induced social influence on social media sites for exchanging multimodal content, and the dissemination of health misinformation and its impact on preventive behaviors. To conduct these studies, Dr. Argyris applies a blend of self-reported methods (population-based surveys and in-vivo experiments), large-scale longitudinal data collection and analyses, and machine-learning based automatic classifications.

Dr. Argyris holds her PhD in Management Information Systems from the Sauder School of Business, University of British Columbia. Prior to coming to 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.

Recent Publications:

· Argyris, Y. A., Muqaddam, A. and Miller, S. (2020) "The Effects of the Visual Presentation of an Influencer’s Extroversion on Perceived Credibility and Purchase Intentions—Moderated by Personality Matching with the Audience," Journal of Retailing and Consumer Services.

· Argyris, Y. A., Wang, Z., Kim, Y., & Yin, Z. (2020). The effects of visual congruence on increasing consumers’ brand engagement: An empirical investigation of influencer marketing on instagram using deep-learning algorithms for automatic image classification. Computers in Human Behavior, doi:10.1016/j.chb.2020.106443

· Argyris, Y. A., Wang, Y. and Muqaddam, A. (2020) "Role of Culture in Engaging Consumers in Organizational Social Media Posts," Journal of Organizational Computing and Electronic Commerce, doi:10.1080/10919392.2020.1823177.

· Argyris, Y. A., Muqaddam, A. and Liang, Y. (2019) “The Role of Flow in Dissemination of Recommendations for Hedonic Products in User-Generated Review Websites,” International Journal of Human Computer Interaction. DOI: 10.1080/10447318.2019.1631543

· Yim, D., Khuntia, J., & Argyris, Y. A. (2018). User Behaviors and Knowledge Exchange in Health Infomediary. In Handbook of Research on Emerging Perspectives on Healthcare Information Systems and Informatics (pp. 213-233). IGI Global.

- Wang, Z., Yin, Z. and Argyris, Y. A. "Detecting Medical Misinformation on Social Media Using Multimodal Deep Learning,” is accepted to the IEEE Journal of Biomedical and Health Informatics, https://doi.org/10.1109/JBHI.2020.3037027 (Impact factor >5). This study centers on the development of a deep learning-based multimodal detector for Instagram anti-vaccine messages (images, texts, and hashtags). To evaluate the proposed model’s performance, a real-world social media dataset that consists of more than 30,000 samples was collected from Instagram between January 2016 and October 2019. Our 30 experiment results demonstrate that the final network achieves above 97% testing accuracy and outperforms other relevant models, demonstrating that it can detect a large amount of antivaccine messages posted daily on social media.

To learn more about Dr. Argyris, visit her website here.