Influence of augmented reality filter selfies on computer-mediated communication

In the context of the increasing prevalence of Computer-Mediated Communication (CMC), visual communication has become a defining feature. The integration of Augmented Reality (AR) technology with smartphone selfies has not only disrupted traditional media patterns but also introduced new challenges and opportunities in communication studies. This research investigates the role of AR filters in CMC and their influence on communication through impression management. Grounded in Goffman's Dramaturgical Theory, Walther's Social Information Processing Theory, and the Hyperpersonal Model, the study constructs a theoretical framework to analyze the effects of AR filter selfies across intrapersonal, interpersonal, and mass communication. Using a qualitative phenomenological approach, data were collected through focus groups (8 groups, 57 participants), in- depth interviews (16 informants), and document analysis. Both the focus group participants and interview informants were students from two universities in Pingdingshan, Henan Province, China. Additionally, document analysis was conducted on 31 records from a selfie competition held at Henan University of Urban Construction. The findings reveal that the combination of AR technology with smartphone selfies integrates photography and computer graphics, blending reality and virtuality, and offering users innovative tools for selective impression management. In intrapersonal communication, AR filter selfies facilitate self-enhancement; in interpersonal communication, they help bridge interaction gaps; and in mass communication, they function as a novel medium that transcends traditional face-to-face interactions. This research not only validates and extends existing theoretical frameworks in the context of emerging media but also provides valuable insights for enhancing social media and communication practices. By elucidating the mechanisms of AR filter communication, this study offers a deeper understanding of online interactions for individuals and organizations.

Text FBMK 2024 68 - Full Text.pdf Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (10MB) Text FBMK 2024 68.pdf Restricted to Repository staff only Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (11MB)

Actions (login required)

View Item