Talking to the Visuals: Exploring Ideology of Generations through Semiotic Landscape of Whatsapp Statuses

  • Mehreen Zafar Lecturer, Department of English, Ghazi University Dera Ghazi Khan, Pakistan
  • Dr. Muhammad Ahsan Lecturer, Department of English, Ghazi University Dera Ghazi Khan, Pakistan
  • Muhammad Naeem Lecturer, Department of English, Ghazi University Dera Ghazi Khan
Keywords: Multimodal Critical Discourse Analysis, Whatsapp Status, Multimodality, Post-Millennials, Millennials and Generation X

Abstract

Whatsapp statuses are an example of computer-mediated communication. The current qualitative and quantitative study aims to explore the ideology of Whatsapp users and highlight the differences among the generations through the semiotic landscape of Whatsapp statuses. The analytical tools of “David Machin and Andrea Mayr” (2012) and theoretical principles of “Kress and Leeuwen” (1996) helped to analyze the multimodal discourse of WhatsApp statuses. A survey was also conducted to know the stance of Whatsapp users. Multimodal Critical Discourse Analysis (MCDA) of 630 Whatsapp statuses of 90 participants in social semiotics represented Post-Millennials, Millennials, and Generation X with clear differences in their ideologies. The differences are louder for gaze, distance, iconography, colors, vector, angle, and frames. The results of the survey show that Post-Millennial give much value to Whatsapp statuses as 92% of them display statuses daily. All three generations have quite separate reasons to use Whatsapp statuses; only informing others is the common reason between Millennials and Generation X. Basically, the users of Whatsapp statuses are the social actors who represent their cognitive meanings socially.

Published
2020-12-26
How to Cite
Mehreen Zafar, Dr. Muhammad Ahsan, & Muhammad Naeem. (2020). Talking to the Visuals: Exploring Ideology of Generations through Semiotic Landscape of Whatsapp Statuses. Research Journal of Social Sciences and Economics Review (RJSSER), 1(4), 1-10. https://doi.org/10.36902/rjsser-vol1-iss4-2020(1-10)