Decoding COVID-19 Conversations with Visualization: Twitter Analytics and Emerging Trends

Abstract

This study delves into the vast landscape of COVID-19 discussions on Twitter, aiming to unveil pertinent insights and emerging trends within this dynamic social media platform. Analyzing a substantial volume of Twitter data related to the pandemic, our research scrutinizes the content, sentiments, and patterns of conversations among users. By employing advanced analytics, we discern key themes, prevalent sentiments, and the evolution of discourse over time. This investigation not only provides a comprehensive overview of the diverse topics encompassed within COVID-19 discussions on Twitter but also sheds light on the trends shaping public opinion and awareness. The abstract scrutinizes the influencers and amplifiers within this virtual discourse, identifying pivotal accounts and trending hashtags that significantly contribute to the dissemination of information. Moreover, the study investigates the geographical and temporal variations in COVID-19 discussions, offering a nuanced understanding of how these conversations evolve across different regions and timeframes. As social media plays an increasingly central role in shaping public perceptions, this research aims to contribute valuable insights for policymakers, health organizations, and the public to comprehend the dynamics of COVID-19 communication on Twitter. Ultimately, by uncovering the insights and trends within these discussions, this study endeavours to enhance our understanding of the public discourse surrounding the pandemic and its implications for public health communication strategies.