Celebrating Excellence, Equally? A Quantitative Analysis of Social Media Posts during the 2024 Paris Olympics and Paralympics

Abstract

This study examines X posts from the 2024 Paris Olympics and Paralympics using natural language processing (NLP) techniques to conduct a comparative analysis of public discourse. While much existing work has focused on language surrounding the Olympics, studies on the Paralympics remain scarce, and none provide a direct comparison of public perception between the two events. This research addresses this gap by applying both topical and sentiment analysis through a diverse set of NLP methods, including Latent Dirichlet Allocation (LDA) for topic modeling, word frequency analysis, Word2Vec for contextual word relationships, and Valence Aware Dictionary and sEntiment Reasoner (VADER) for sentiment classification and temporal trends. Six datasets are created, consisting of X posts from the Olympic and Paralympic Games, covering both English- and French-language discussions, as well as posts from the general public and the o fficial Olympic and Paralympic X accounts. By analyzing differences in language and sentiment across these datasets, this study explores how perceptions of the two global sporting events vary across cultures and between public discourse and institutional narratives.