How Do Social Media Machines Affect Self-Concept Research? : Systematic Literature Review of the Latest Trends

Fehér, Katalin and Katona, Attila I. (2023) How Do Social Media Machines Affect Self-Concept Research? : Systematic Literature Review of the Latest Trends. KOME: AN INTERNATIONAL JOURNAL OF PURE COMMUNICATION INQUIRY, 11 (1). pp. 2-27. ISSN 2063-7330

Preview

Text 01_feher-katona_2-27_KOME_2023_01.pdf Available under License Creative Commons Attribution. Download (3MB) | Preview

Abstract

Advanced digital technologies broadly penetrate self-activities, such as algorithms, machine learning, or artificial intelligence. This trend is most evident on social media, where contents, attitudes and evaluative judgments meet on technology-driven platforms. Moreover, human networks also started communicating with social bots or conversational interfaces. All these challenges can trigger a redesign of self-concept via technology. Therefore, the paper investigates how social media machines affect self-concept-related academic research. First, pioneers of the field are presented. Second, the self-concept research in digital technology and social media is summarised. Topic networks illustrate critical research fields with the latest trends and future implications. Last but not least, we also investigate how emerging media phenomena affect academic trends in the case of social bots or fake news. The study aims to support the connected research in psychology, business, management, education, political science, medicine and media studies with an understanding of the latest trends. The additional goal is to highlight the potential of market-based research cooperation with academia supporting significant developments and funding.

Actions (login required)

Edit Item