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.

翻译：这项研究的目的是通过分析地方政府选举期间在Twitter上分享的情感来理解南非的政治背景,分析的重点是了解围绕四个主要政党ANC、DA、EFF和ActionSA的讨论。采用了半监督的方法,采用基于图表的技术,将大量可获取的Twitter数据贴上标签,将Twitter分类为负面和积极情绪。通过潜在专题提取进一步分析了表达负面情绪的推文,以发现与每个政党有关的隐性关注话题。我们的调查结果表明,南非所有推特用户的普遍情绪对所有四个主要政党都是负面的,用户对现任执政党ANC的负面情绪预测最强烈,涉及围绕腐败、无能和充斥的顾虑。