  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 cantered around corruption, incompetence and loadshedding.
