Social Media and the COVID-19: South African and Zimbabwean Netizens’ Response to a Pandemic

Since the end of 2019, world faced a major health crisis in form Coronavirus (COVID-19) pandemic. To mitigate impact pandemic, governments across globe instituted measures such as restricting local and international travel many cases, ordering citizens to stay indoors. Considering social economic these restrictions it becomes crucial investigate internet citizens’ (netizens) perception about precautionary adopted. The study is anchored digital public sphere theory, which treats media applications virtual platforms where netizens commune share ideas debate issues that affect them. Social already have critical views on current However, majority this data unstructured difficult interpret. Natural language processing (NLP), other hand, makes task gathering analysing vast amounts textual feasible. Extracting structured knowledge from natural language, however, comes with unique challenges due diverse linguistic properties including abbreviation, spelling mistakes, punctuations, stop words non-standard text. In work, Latent Dirichlet Allocation (LDA) algorithm was applied tweeter extract topics discussed by netzens Zimbabwe South Africa. primary focus paper, comparatively explore variety occupied twitter communities two countries. We examine whether or not national identities define differentiate countries also exist Twitter evident emerging topics. Furthermore, work investigated opinion how discuss around COVID-19 pandemic