An Analysis of Middle Eastern Female Athletes’ Visual Self-Presentation Strategies on Instagram During the Tokyo 2020 Olympics
Year: 2025
Type: article
Abstract: The presentation of athletes through social media platforms is an essential consideration in constructing an athlete's overall media presence.Traditional media channels provide an unfair advantage to male athletes and sporting events.Female athletes, therefore, are increasingly recognizing the value of social media channels in creating their brands and developing opportunities to obtain sponsorships and endorsements.This challenge intensifies in diverse cultural contexts.This study explores how female athletes from the MENA region use Instagram as a visual self-presentation platform to construct their personal brand during a major sporting event-the 2020 Tokyo Olympic Games.An analysis is performed on a purposeful collection of photographs from sixteen athletes, enabling a better understanding of how athletes can develop their personal image to attract fans and sports stakeholders.Research into personal branding generally lacks representation of athletes from the MENA region, and this study contributes to the limited range of outcomes related to MENA athletes.Goffman's self-presentation theory is used as a framework to guide the analysis of Instagram images.The results show that, during a major sporting event in the MENA region, female athletes tend to share more photographs of their athletic performance and their countries, resulting in increased traffic to their Instagram accounts.The high frequency of photographposting occurred during the competition itself, not before or after.Many athletes do not post photographs about their personal or social lives, nor do they pay adequate attention to potential sponsors or businesses.
Authors: Jailan El Bous, Darren Mundy
Institution: University of Hull
Language: English
Topic: Sports, Gender, and Society
Subfield: Gender Studies
Field: Social Sciences
Domain: Social Sciences
SDG: Gender equality
Open Access status: hybrid
OpenAlex ID: W4412408923
