(untitled) (Journal of the Digital Humanities Association of Southern Africa, 2024)
This study investigates the prevalence of evictionsin South Africa and examines potential disparitiesbetween traditional media reporting and socialmedia discourse. Employing a sentiment analysisframework, we extend its application to comparethe reporting of evictions in newspaper articles(i.e. conventional media) and Twitter data (i.e.social media). Statistical machine-learningmethods are utilized to predict sentiment scoresfor both types of content, and a chi-square test isemployed to evaluate bias between news articlesand tweets. The test results reveal a significant biasin the sentiment distribution, suggesting that thedissimilarities observed between articles andtweets are not merely coincidental.