This paper presents a conceptual overview of traditional readability metrics adapted for two South African Indigenous languages, isiZulu and Sesotho, which differ orthographically with conjunctive and disjunctive writing systems, respectively. Both languages are low-resource, lacking extensive corpora, lexicons, and pretrained models necessary for automatic readability assessment. By critically examining these adaptations, we highlight the challenges of applying English-based metrics to morphologically complex African languages and emphasise the need for language-specific digital resources that reflect local linguistic structures. Our work aligns with ongoing efforts to develop and enhance language resources for under-resourced African Indigenous languages, thereby supporting their evolving presence and accessibility in the digital age, including contexts shaped by large language models.

This article presents Vibes, a prototype interface for visualising multilingual online discourse in Southern Africa. We developed the prototype during a three-day hackathon with a multidisciplinary team. The interface combines computational tools, manual coding and visualisation methods to work with data that standard NLP tools cannot process due to their monolingual design. We tested Vibes on two YouTube datasets: English/isiXhosa comments from the @cmtvsa channel and comments on videos discussing a hair product advertisement controversy. Through this work, we encountered practical challenges, including language identification failures, code-switching within single posts, non-standard orthographies, and multimodal communication through emojis. The challenges led us to propose an interface for collaborative coding that accounts for translanguaging practices. The hackathon development process highlighted the need for context-sensitive tools to study linguistic diversity in the Global South.

Digital Humanities scholarship is often framed through paradigms developed in the Global North, leaving African-specific practices and epistemologies underexplored. In this article, I use topic modelling and lexical analysis to investigate what constitutes African DH by analysing 41 Southern African DH articles. The findings indicate that the majority of publications in JDHASA engage deeply with language-related topics. The field combines advanced computational methods with a strong grounding in local languages, cultural heritage, and socio-historical realities. It also reflects responsiveness to evolving digital social realities, addressing themes such as online harm, misinformation, and affective communities. This article contributes to the theorisation of African DH by identifying thematic tendencies and methodological patterns specific to the Southern African context. It highlights the dual focus on computational innovation and cultural rootedness, offering an empirically grounded foundation for further critical engagement with what African DH is and what it can become.

It is with immense pride and anticipation that we introduce the fifth volume of the Journal of Digital Humanities Association of Southern Africa (JDHASA), centred on the theme “Digital Humanities for Inclusion.”

Although romantic deception is prevalent in many societies, it may not be readily acceptable to publicly acknowledge approval of acts associated with such deception. This article explores the publicly acknowledged sentiments of viewers of two YouTube channels aimed at the exposure of romantic deceit through two shows for facilitating a “couple switching phones” game. Specifically, we analyse videos where all participants are caught engaging in extra-relationship affairs. Our study reveals a prevailing trend of neutral comments from viewers, indicating a reluctance to openly acknowledge approval or disapproval of the depicted acts. Interestingly, the discussions primarily revolve around tribal issues [specially focused on the Xhosa tribe] rather than focusing on the subject of romantic deception itself.

This article addresses the scarcity of gold-standard annotated corpora for readability assessment in Sesotho, a low-resource language. As a solution, we propose using translated texts to construct a readability-labelled corpus. Specifically, we investigate the feasibility of using Google Translate to translate texts from Sesotho to English and then manually post-editing the texts. We then evaluate the effectiveness of the Google translations by comparing them to the human-post-edited versions. We utilised the Ghent University readability demo to extract the readability levels of both the Google translations and the human-post-edited translations. The translations are then evaluated using three evaluation metrics, namely, BLEU, NIST, and RIBES scores. The translation evaluation results reveal substantial similarities between the machine translations and the corresponding human-post-edited texts. Moreover, the results of the readability assessment and the comparison of text properties demonstrate a high level of consistency between machine translations and human-post-edited texts. These findings suggest that Google Translations show promise in addressing challenges in developing readability-labelled parallel datasets in low-resource languages like Sesotho, highlighting the potential of leveraging machine translation techniques to develop translated corpora for such languages. The evaluation of Google Translations in the context of educational texts in Sesotho and the demonstration of the feasibility and potential of using machine translations for enhancing readability in Sesotho will aid in the quest for developing Sesotho text readability measures.