Abstract:
This study aims to understand the South African political context
by analysing the sentiments shared on Twitter during the local
government elections. An emphasis on the analysis was placed
on understanding the discussions led around four predominant
political parties – ANC, DA, EFF and ActionSA. A semi-supervised
approach by means of a graph-based technique to label the vast
accessible Twitter data for the classification of tweets into negative
and positive sentiment was used. The tweets expressing negative
sentiment were further analysed through latent topic extraction
to uncover hidden topics of concern associated with each of the
political parties. Our findings demonstrated that the general sentiment
across South African Twitter users is negative towards all
four predominant parties with the worst negative sentiment among
users projected towards the current ruling party, ANC, relating to
concerns centered around corruption, incompetence and loadshedding.
