The depiction of Orania in the media (2013-2022): A quantitative analysis using Natural Language Processing (NLP)

The current article investigates the depiction of the town of Orania in the media. Being an exclusive Afrikaner town, this town is highly controversial and is often seen as a remnant of apartheid, leading residents of this town to form the perception that the media treats them unfairly. Using Natural Language Processing (NLP) techniques, namely a lexicon-based sentiment analysis classification and a machine-learning political bias classification, it is shown that the vast majority of news reports and opinion pieces on this town exhibit minimal political bias, and publications on this town are evenly distributed between left and right political bias. In addition, while the majority of news reports and opinion pieces published on this town are neutral, more publications are positive than negative. However, differences in the depiction of this town based on the language of publications are also discussed, with English publications more negative and Afrikaans publications more positive, and the majority of publications on this town are in Afrikaans. Overall, the study finds that while some individual publications present Orania in a very negative light, in general, the media reports on this town in a balanced way

Sticks and Stones May Break My Bones but Words Will Never Hurt Me...Until I See Them: A Qualitative Content Analysis of Trolls in Relation to the Gricean Maxims and (IM)Polite Virtual Speech Acts

The troll is one of the most obtrusive and disruptive bad actors on the internet. Unlike other bad actors, the troll interacts on a more personal and intimate level with other internet users. Social media platforms, online communities, comment boards, and chatroom forums provide them with this opportunity. What distinguishes these social provocateurs from other bad actors are their virtual speech acts and online behaviors. These acts aim to incite anger, shame, or frustration in others through the weaponization of words, phrases, and other rhetoric. Online trolls come in all forms and use various speech tactics to insult and demean their target audiences. The goal of this research is to investigate trolls\u27 virtual speech acts and the impact of troll-like behaviors on online communities. Using Gricean maxims and politeness theory, this study seeks to identify common vernacular, word usage, and other language behaviors that trolls use to divert the conversation, insult others, and possibly affect fellow internet users’ mental health and well-being