REIMAGINING GENDER NARRATIVES: A SENTIMENT ANALYSIS OF EVOLVING REPRESENTATION OF FEMALE CELEBRITIES THROUGH X POSTS

Abstract

The present study examines gender narratives represented online through X and the statistical analysis of the collected sentiment patterns of the given corpus. This metafunctional approach studies that language shapes the perception of reality and expresses the worldview. The study aims to highlight dominant sentiment patterns in public replies to female celebrities. The research has used mixed methods for data analysis. X data retrieved through the X API has been analyzed and interpreted with the support of Systemic Functional Linguistics (SFL) of Michael Halliday (1978), which provides a framework for examining the functional features of language. By analyzing a comprehensive dataset of X posts mentioning prominent female figures, the study aims to understand how the language and emotional tone surrounding these celebrities have evolved. The findings suggest how fans of renowned female celebrities use social media to express their views regarding inclined positive sentiment patterns and opinions regarding those public female figures. This reimaging involves female celebrities to gain insight into the impact of traditional media on social media perceptions. Social media has aptly highlighted the diversified perceptions of males regarding females in general and female celebrities in particular. Gender roles and stereotypes have been reimagined since the use of social media platforms like X (in the present case). This study has left a gap for further researchers to understand how attitudes towards female celebrities have evolved over longer time span of say, ten years, paying particular attention to changes associated with significant life events, professional turning points, or public controversy of the celebrities