The Social Media Landscape: A Multimodal Discourse Analysis of Representations of Women Characters

Abstract

The present research focuses on the widespread phenomenon of creating and sharing short video clips, commonly known as "reels," within the digital landscape of social media. These reels have become an integral part of how people express themselves and have fun online. However, the issue emerges that many of these reels conform to prevalent gender stereotypes, particularly in how they portray women which may have implications on how people view themselves and interact with others keeping in view the gender equality. Following the theory of multimodality, this research intends to uncover the applied reflections behind the creation and consumption of gender- stereotypical content in the selected reels. It also explores broader consequences, such as how these stereotypes influence people's self-esteem, mental well-being, and how they relate to one another. Ten reels have been collected through non-random sampling from social media platforms: Instagram and Facebook. Most of the reels were taken keeping in view the followers and likes not less than 5000. The selected data was analyzed using multimodal analysis following theoretical framework of Kress and Van Leeuwen (1996, 2006). The research provides specific recommendations to mitigate the effects of gender-stereotypical content in these online videos. This research seeks to shed light on these complexities and pave the way for a more inclusive and fairer online environment.