Abstract
This study inves
tigates the prevalence of evictions
in South Africa and examines potential disparities
between traditional media reporting and social
media discourse. Employing a sentiment analysis
framework, we extend its application to compare
the reporting of evictions in newspaper articles
i.e. conventional media) and Twitter data ( i.e.
social media). Statistical machine learning
methods are utilized to predict sentiment scores
for both types of content, and a chi square test is
employed to evaluate bias between news articles
and tweets. The test results reveal a significant bias
in the sentiment distribution, suggesting that the
dissimilarities observed between articles and
tweets are not merely coincidental.