Journal of the Digital Humanities Association of Southern Africa (DHASA)
The Journal of the Digital Humanities Association of Southern Africa (DHASA), ISSN 3006-6492, which publishes from 2022, is the peer-reviewed open-access journal of DHASA. Since its foundation in 2016, DHASA has become the official network of digital humanities scholars in Southern Africa. DHASA members come from a wide variety of fields in the humanities, social sciences, and computer sciences. The DHASA Journal is an important initiative aimed at making the research output of our members and other interested scholars publicly available. If you are interested in joining DHASA, please follow this link.
The sixth workshop on Resources for African Indigenous Languages (RAIL) was held on 10 November 2025 at the CSIR International Convention Centre in Pretoria, South Africa. It was co-located with the Digital Humanities Association of Southern Africa (DHASA) 2025 conference, which took place from 11 to 14 November 2025
Copyright (c) 2025 Mmasibidi Setaka-Bapela, Rooweither Mabuya, Muzi Matfunjwa, Menno van Zaanen https://creativecommons.org/licenses/by-sa/4.0
This is the preface for the conference of the Digital Humanities Association of Southern Africa (DHASA2025), which took place from the 10-14 November 2025.
Copyright (c) 2025 Ilana Wilken https://creativecommons.org/licenses/by-sa/4.0
Siswati Part of Speech Tagger: A Quantitative Evaluation
This article evaluates the performance of the Siswati Text Annotation Tool part of speech (STAT POS) tagger using Recall, Precision and F1 score metrics. A quantitative research design was adopted for analysis, and data was collected through purposive sampling. Python 3 was utilised to calculate the Recall and Precision of the STAT POS tagger outputs. The results show that the Recall for nouns was 0.761, Precision 0.417, with an F1 score of 0.54; for verbs, the Recall was 0.756, Precision 0.798 and F1 score 0.54; for adverbs, the Recall was 0.571, Precision 0.8, and F1 score 0.67; for possessives, the Recall was 0.963, Precision 0.813 and F1 score 0.88. For relatives (REL), the Recall was 0.706, Precision 0.523, and the F1 score 0.60; for class-indicating demonstratives, the Recall was 0.333, Precision 0.25, and the F1 score 0.29; and for copulatives (COP), the Recall was 0.75, Precision 0.75, and the F1 score 0.75. For conjunctions, the Recall was 0.85, the Precision was 0.68, and the F1 score was 0.76; for pronouns, the Recall was 0.563, the Precision was 1.0, and the F1 score was 0.72; for adjectives, the Recall was 0.75, the Precision was 0.75, and the F1 score was 0.75. However, question words, interjections and ideophones received 0.0., highlighting the need for refinement of the STAT POS tagger.
Copyright (c) 2025 Muzi Matfunjwa https://creativecommons.org/licenses/by-sa/4.0
Ideational Analysis and Integration of African Folktale in Science, Technology, and Education
Folktales are literary forms that reveal the soul of any society; they express its wishes, desires, hopes, and beliefs about the world. They have fictional characters and situations, mostly oral traditions, before they were written down. According to Cynthia McDaniel (1993), folktales can be used in all disciplines to convey knowledge and communicate ideas; they serve as an inherent vehicle for intergenerational communication that prepares and assigns roles and responsibilities to different generations in their communities. They are more pedagogic devices and less literary pieces. They cultivate universal values such as compassion, generosity, and honesty while disapproving of attributes such as cruelty, greed, and dishonesty. To illustrate McDaniel's claims, this paper will firstly use the ideational metafunctional framework found in Systemic Functional Linguistics, which expresses the clausal experiences and content from a grammatical perspective, coupled with syntagmatic analysis, which describes the text (folktale) in chronological order as reported by the storyteller. Secondly, the presentation will use a textual metafunctional framework that fulfills the thematic function of the clause, coupled with the paradigmatic analysis where the folkloristic text's patterns are regrouped more analytically to reveal the text's latent content, or theme. The Voyant Tool, a web-based text reading and analysis environment designed to facilitate the analysis of various text formats, was used to extract and analyze data from a Sesotho folktale to illustrate how folktales may be integrated with technology for research and educational purposes. This paper employed a descriptive research design that incorporates qualitative (content analysis) and quantitative (statistical analysis) methodologies to analyze and interpret the story. It is observed, through the Voyant tool, that the story is built out of 191 Sesotho word formations, and through the ideational analysis, that the storyteller employed more material process types than mental process types, and lastly, with the textual interpretation, indicating the value of oral literature in our daily lives as well as the significant role folktales may play in interpreting sociopolitical events in contemporary communities.
Copyright (c) 2025 Elias Malete https://creativecommons.org/licenses/by-sa/4.0
Building Corpora for Low-Resource Kenyan Languages
Natural Language Processing is a crucial frontier in artificial intelligence, with broad application across public health, agriculture, education, and commerce. However, due to the lack of substantial linguistic resources, many African languages remain underrepresented in this digital transformation. This article presents a case study on the development of linguistic corpora for three under-resourced Kenyan languages, Kidaw’ida, Kalenjin, and Dholuo, with the aim of advancing natural language processing and linguistic research in African communities. Our project, which lasted one year, employed a selective crowd-sourcing methodology to collect text and speech data from native speakers of these languages. Data collection involved (1) recording and transcribing conver- sations and translating the resulting text into Kiswahili, creating parallel corpora, and (2) reading and recording written texts to generate speech corpora. We made these resources freely accessible on open-research platforms, namely Zenodo for the parallel text corpora and Mozilla Common Voice for the speech datasets, thereby facilitating ongoing contributions and developer access to train models and develop Natural Language Processing applications.
Copyright (c) 2025 Audrey Mbogho, Quin Awuor, Andrew Kipkebut, Lilian Wanzare, Vivian Oloo https://creativecommons.org/licenses/by-sa/4.0
Stop word lists are useful resources that allow for the filtering of words in texts that typically do not carry (much) content. Filtering stop words can improve the efficiency and accuracy of data processing. Stop words are typically short and occur very frequently in texts. Stop word lists are language dependent and many low-resource languages currently do not have (accurate) stop word lists. In this article, we look at how we can create, based on word frequency, a stop word list for Khoekhoe, which is a low-resource language spoken in Southern Africa. Given that stop words do not carry much content, they can be expected to occur consistently across different texts. We compare lists of most frequent words between texts in different genres and which words feature in these lists consistently. We look at the overlap of frequent words in English texts and compare these to a known English stop word list as well, and compare the results with the overlap of frequent words in Khoekhoe texts. The results show that there is a high overlap between genres for English, but the overlap between the Khoekhoe genres is lower. This may be due to a different typological profile of Khoekhoe. This means that creating a stop word list for Khoekhoe is more complicated and most likely requires other techniques to produce a useful stop word list.
Copyright (c) 2025 Menno Van Zaanen, Alena Witzlack-Makarevich https://creativecommons.org/licenses/by-sa/4.0
Creating Bilingual Corpora for isiZulu: A Case Study from the University of KwaZulu-Natal
Although several bilingual resources exist, there is a lack of domain-specific, institutionally verified parallel corpus focusing on academic and administrative texts. Existing datasets such as Autshumato English–isiZulu corpus, UNISA English/Zulu Parallel Corpus, and the WebCrawl African Corpus hosted on GitHub provide valuable material but differ in accessibility, domain coverage, and documentation. To complement these initiatives, the University Language Planning and Development Office (ULPDO) at the University of KwaZulu-Natal has developed a curated isiZulu–English Parallel Corpus comprising 10,000 carefully aligned sentence pairs drawn from institutional and academic texts. This paper outlines the corpus compilation process, including data sourcing, cleaning, alignment, and validation, and discusses key structural and linguistic challenges encountered. The resource contributes to translation studies, terminology development, and multilingual natural language processing, while supporting ongoing efforts to advance the digital presence and intellectualisation of isiZulu.
Copyright (c) 2025 Thandeka Mbali Gumede, Rooweither Mabuya, Njabulo Hadebe https://creativecommons.org/licenses/by-sa/4.0
Traditional Readability Approaches in Sesotho and isiZulu
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.
Copyright (c) 2025 Johannes Sibeko, Mthuli Buthelezi https://creativecommons.org/licenses/by-sa/4.0
An exploration of the computational identification of English loan words in Sesotho
South Africa, with its twelve official languages, is an inherently multilingual country. As such, speakers of many of the languages have been in direct contact. This has led to a cross-over of words and phrases between languages. In this article, we provide a methodology to identify words that are (potentially) borrowed from another language. We test our approach by trying to identify words that moved from English into Sesotho (or potentially the other way around). To do this, we start with a bilingual Sesotho-English dictionary (Bukantswe). We then develop a lexicographic comparison method that takes a pair of lexical items (English and Sesotho) and computes a range of distance metrics. These distance metrics are applied to the raw words (i.e., comparing orthography), but using the Soundex algorithm, an approximate phonological comparison can be made as well. Unfortunately, Bukantswe does not contain complete annotation of loan words, so a quantitative evaluation is not currently possible. We provide a qualitative analysis of the results, which shows that many loan words can be found, but in some cases lexical items that have a high similarity are not loan words. We discuss different situations related to the influence of orthography, phonology, syllable structure, and morphology. The approach itself is language independent, so it can also be applied to other language pairs, e.g., Afrikaans and Sesotho, or more related languages, such as isiXhosa and isiZulu.
Copyright (c) 2025 Mmasibidi Setaka, Menno Van Zaanen https://creativecommons.org/licenses/by-sa/4.0
SeSoDa: A Compact Context-Rich Sesotho-English Dataset for LoRA Fine-Tuning of SLMs
We introduce SeSoDa, a multidomain Sesotho(Sa Lesotho)-English dataset of 1,966 prompt-completion pairs that span six categories (nouns, verbs, idioms, quantifiers, grammar rules, usage alerts). SeSoDa documents the morphosyntactic complexity, uncaptured Basotho cultural specificity, and orthographic/phonological differences between Lesotho and South African Sesotho. We created a user-friendly, JSON-style corpus with detailed metadata. This aims to lower the technical barrier for new researchers in Lesotho, helping them advance culture-aware machine translation, linguistic analysis, and cultural preservation using AI. As a proof of concept, we demonstrate SeSoDa’s utility by fine-tuning the TinyLlama-1.1B-Chat model using Low-Rank Adaptation (LoRA) on entirely free Google Colab GPUs and runtime limits. This parameter efficient fine-tuning approach is particularly vital for resource-constrained environments like Lesotho, making advanced NLP model adaptation feasible and accessible without requiring extensive computational resources. We open-source the code for the dataset creation, the baseline model, and the dataset itself. We hope to see both Basotho researchers and developers build on top of our effort
Copyright (c) 2025 Mandla Motaung, Graham Hill, Moseli Mots'oehli https://creativecommons.org/licenses/by-sa/4.0
Using the isiZulu GF Resource Grammar for morphological annotation
The isiZulu GF Resource Grammar (ZRG) enables syntactic parsing using the GF runtime system. In order to perform this task, the ZRG implicitly encodes rich morphosyntactic information about isiZulu. In this paper we show how such information can be made explicit by adapting the way the grammar linearises GF abstract syntax trees. The result is annotated text, which can be utilised in various ways for supporting natural language processing of an under-resourced, morphologically complex language like isiZulu.
Copyright (c) 2025 Laurette Marais, Laurette Pretorius https://creativecommons.org/licenses/by-sa/4.0
Multilingual Data from the Agricultural Domain: Presenting the NWU-Pula/Imvula Corpora
This paper presents new multilingual corpora from the agricultural domain for seven South African Languages, namely Afrikaans, English, isiXhosa, isiZulu, Sesotho, Sesotho sa Leboa, and Setswana, based on the Pula/Imvula magazine. After pre-processing, the data has been automatically sentencized, tokenized, lemmatized and annotated with part-of-speech information using the services available at https://v-ctx-lnx7.nwu.ac.za/. The final resources comprising between 774k and 1,38M tokens per language are included on the Corpus Cooperative at North-West University (COCO@NWU) corpus platform at https://coco.nwu.ac.za/ as searchable corpora. In addition, the data can be made avail- able as text files for research purposes upon request. To highlight the value of this agricultural domain-specific data collection in relation to more general data, we also include some corpus-based statistics and comparisons with previous research.
Copyright (c) 2025 Tanja Gaustad, Cindy McKellar, Martin J. Puttkammer https://creativecommons.org/licenses/by-sa/4.0
Bootstrapping Siswati lexical resources from isiZulu
IsiZulu and Siswati are closely related languages that share significant morphosyntactic characteristics. Systematic differences between these languages have been identified at the phonological and morphosyntactic levels. Due to the resource-scarce status of these languages, this similarity has led to bootstrapping of computational language resources at the morphological and syntactic levels. In this work, we investigate the feasibility of adapting lexical items in a computational lexicon from isiZulu to Siswati. We use Grammatical Framework resource grammars for both languages to analyse and transform lexical items, which are then evaluated against a parallel term list. An iterative process yields a success rate of 70.5 %, indicating that this approach is largely viable as a means of significantly reducing the manual effort needed to develop lexicons for computational resources for Siswati.
Copyright (c) 2025 Roné Wierenga, Laurette Marais, Ilana Wilken https://creativecommons.org/licenses/by-sa/4.0
Multimodal Classification System for Hausa Using LLMs and Vision Transformers
This paper presents a classification-based Vi- sual Question Answering (VQA) system for the Hausa language, integrating Large Language Models (LLMs) and vision transformers. By fine-tuning LLMs on monolingual Hausa text and fusing their representations with those of state-of-the-art vision encoders, our system pre- dicts answers from a fixed vocabulary. Exper- iments conducted on the HaVQA dataset, un- der offline text–image augmentation regimes, tailored to the specificity of Hausa as a low- resource language, show that this augmentation strategy yields the best performance over the baseline, achieving 35.85% accuracy, 35.89% WuPalmer similarity, and 15.32% F1-score.
Copyright (c) 2025 Ali Mijiyawa, Fatiha Sadat https://creativecommons.org/licenses/by-sa/4.0
Mafoko: Structuring and Building Open Multilingual Terminologies for South African NLP
The critical lack of structured terminological data for South Africa’s official languages hampers progress in multilingual NLP, despite the existence of numerous government and academic terminology lists. These valuable assets remain fragmented and locked in non-machine-readable formats, rendering them unusable for computational research and development. Mafoko addresses this challenge by systematically aggregating, cleaning, and standardising these scattered resources into open, interoperable datasets. We introduce the foundational Mafoko dataset, released under the equitable, Africa-centered NOODL framework. To demonstrate its immediate utility, we integrate the terminology into a Retrieval-Augmented Generation (RAG) pipeline. Experiments show substantial improvements in the accuracy and domain-specific consistency of English-to-Tshivenda machine translation for large language models. Mafoko provides a scalable foundation for developing robust and equitable NLP technologies, ensuring South Africa’s rich linguistic diversity is represented in the digital age.
Copyright (c) 2025 Vukosi Marivate, Isheanesu Joseph Dzingirai, Fiskani Banda, Richard Lastrucci, Thapelo Sindane, Keabetswe Madumo, Kayode Olaleye, Abiodun Modupe, Unarine Netshifhefhe, Herkulaas Combrink, Mohlatlego Nakeng, Matome Ledwaba https://creativecommons.org/licenses/by-sa/4.0
Compiling Specialised Glossaries: A Case Study of English-isiNdebele Medical Terms
The inability to access health care because of a language barrier is a matter of concern which this study seeks to address. There is a critical need to access health care communication by amaNdebele, an ethnic group who speak Southern Ndebele known as isiNdebele, one of the official languages of South Africa. IsiNdebele belongs to the Nguni family, alongside isiZulu, isiXhosa and Siswati. The study examines the compilation of a specialised English-isiNdebele glossary of medical terms. It investigates the methodologies and challenges that are involved in the creation of bilingual medical terminologies for English and isiNdebele. A corpus-based approach together with the prescriptive and descriptive lexicographic methods was employed. Medical corpora were compiled, and consultation with the isiNdebele speaking medical community also took place. This was done so that medical terms which are culturally appropriate could be developed. The findings of this study reveal notable gaps in the medical terminology of isiNdebele. The findings further emphasise the significance of term formation in which the medical community (nurses and doctors) and language (isiNdebele) experts are involved. This study contributes to the broader discourse on equity in healthcare. It also contributes to the intellectualisation of African languages in post-apartheid South Africa.
Copyright (c) 2025 Nomsebenzi Malele https://creativecommons.org/licenses/by-sa/4.0
Introducing the Historical African Languages Database: A Translingual Resource of Crosslinked Dictionaries
The earliest written documentation of most African languages comes in the form of dictionaries and field notes prepared by European missionaries and linguists, with the assistance of African informants, in the nineteenth and early twentieth centuries. These resources have been difficult to access and compare, existing only in either print or unprocessed scans. We present a fully searchable and interconnected online database that makes such resources more easily accessible for study. It currently contains seven bilingual dictionaries, with many more sources to be added as they are processed. We explain the database’s design, in which processed entries are separated and their fields tagged according to a consistent structure, maximizing query options and facilitating translingual connections. We describe the functionality of the website through which users can access the data in a variety of ways. We discuss the database’s construction process, including particular challenges related to these historical data sources, and outline the development of a scalable procedure for its future expansion. We also present three case studies illustrating potential uses of the database by historians, linguists, and educators. Finally, we identify a roadmap for the resource’s continued improvement through additional features.
Copyright (c) 2025 James Law, Daren E Ray, Earl Kjar Brown https://creativecommons.org/licenses/by-sa/4.0
Multilingual vibes: Visualising linguistic resources and emoji in Southern African online discourse
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.
Copyright (c) 2025 Zelalem Shibeshi, Marion Walton, Johannes Sibeko, Vusi Maxwell Mthembu, Henri-Count Evans, Nkazimlo Ngcungca, Alette Schoon https://creativecommons.org/licenses/by-sa/4.0
Social Mobility and Phonetic Change in South African Indian English: Retroflexion and GOOSE-Fronting in Potchefstroom and Mohadin
This paper examines linguistic variation in South African Indian English (SAIE) as part of a broader effort to document and digitally preserve marginalized voices in post-apartheid South Africa. Focusing on Potchefstroom and the historically segregated township of Mohadin, the study investigates two key phonetic variables: retroflexion and the GOOSE vowel. The analysis is based on 32 speakers stratified by age, gender, and social class. Data were collected through Labovian sociolinguistic interviews and analyzed using PRAAT and RStudio. Welch’s t-tests and conditional inference trees (ctrees) were used to explore how inter-ethnolinguistic mobility, gender, and social class shape phonetic variation. Results reveal significant sociophonetic shifts, with younger speakers and women in Potchefstroom leading a move towards more standardized English pronunciations, while older women in Mohadin maintain traditional speech patterns. By combining rigorous quantitative sociophonetics with digital analytical tools, this research highlights the potential of Digital Humanities to document and amplify marginalized linguistic identities. It contributes to ongoing discussions on decolonizing knowledge by foregrounding under-researched communities and demonstrating how digitally archived linguistic data can inform inclusive and culturally grounded models of language change and variation.
Copyright (c) 2025 Angel Nyoni, Ian Bekker, Alfred Kondoro https://creativecommons.org/licenses/by-sa/4.0
Using Content Analysis to Explore AmaXhosa Language Identities in Social Media Texts
In the age of increasing digital participation, the role of social media in shaping and revealing identity has become an important area of scholarly inquiry. This article explores the viability of content analysis as a method for inferring identity markers of amaXhosa in multilingual online discourse, focusing on isiXhosa- and English-dominant YouTube comments. Draw ing on the theoretical framework of performativity, the study examines how amaXhosa construct and express cultural and linguistic identities through language use in digital spaces shaped by English dominance. A curated selection of 80 YouTube videos related to isiXhosa culture, interviews, and pranks was analysed. Comments were mined using the YouTube API, and the South African Language Identification Tool (SA-LID) was applied for language cate gorisation. By grounding its approach in local language use and identity, the study contributes to African sociolinguistics and the broader field of African Digital Humanities, demonstrating how social media data can inform context identity research in multilingual societies.
Copyright (c) 2025 Nkazimlo Ngcungca https://creativecommons.org/licenses/by-sa/4.0
Creative AI: Prompting Portraits and Matching Datasets
This paper aims to provide a brief exploration of two versions of Creative AI, namely the prompting of portraits by using AI text-to-image generators and the use of GAN, AICAN and Facer to create AI generated portraits. These two versions are in turn compared to corresponding debates in the field of art history, namely the image-text debate as positioned by the image scholar, WJT Mitchell, followed by the concept of schemata as proposed by the art historian EH Gombrich. First, Mitchell’s understanding of the nature of the image versus text is utilized to compare portraits prompted through text-to-image generators. Secondly, Gombrich’s schemata is compared with recent AI portraits generated by means of image datasets. The differences between the art historical and the Creative AI processes are explored to draw initial conclusions about the future of portraiture and creativity.
Copyright (c) 2025 Amanda du Preez https://creativecommons.org/licenses/by-sa/4.0
Following Digital Footprints: Researching South African Digital Poetry
Contemporary scholarship increasingly recognises the need to document the growing corpus of African literature being produced and distributed via social media and other online platforms. In African literature and the future, Ogundipe (2015) declared that: In the search for a viable path for the future of African literature, a well-crafted vision of the future and effective strategies to engender transformation are imperative. This raises the practical application of the digital space, the internet and related innovative technology as new paradigms of knowledge to African literary engagement. But the absence of a critical standard remains a bane of this development. To address this critical imperative and further explore the prevalence of such works, I collected a dataset to find examples of literary trends and key recent examples of significant works, informed by Moretti's scholarship on distant reading. The dataset focuses on poetry written by younger South African authors from the Born Free Generation, in line with my broader research. The main purpose of this paper is to present my findings and the theoretical and methodological framework that informed them. The paper concludes by briefly proposing some possible means of expanding this research and proposing a large-scale online archival project.
Copyright (c) 2025 Jasmine Mattey https://creativecommons.org/licenses/by-sa/4.0
Mapping Intersectionality: Geospatial Narratives and Digital Activism in Chioma Okereke’s Water Baby
This study uses spatial and intersectional theory to analyse Chioma Okerekes Water Baby (2024), which illustrates the realities of Makoko, Lagoss neglected waterfront community. Through its young protagonist, Baby, the novel uncovers themes of gender exclusion, resilience, and visibility in a context of displacement and creativity. Employing literary analysis in conjunction with digital tools such as Voyant and StoryMapJS, the research links Okerekes story to real locations in Makoko, such as Adogbo, Yanshiwhe and Sogunro. A field visit in October 2025 gathered visual and spatial data that affirmed the setting of the novel while highlighting environmental and health issues not addressed in the text. Some residents expressed concerns about photography without consent, reflecting ethical dilemmas in documenting marginalised areas. The findings suggest that Water Baby serves as a literary counter mapping tool that reclaims erased geographies, confronts invisibility, and preserves cultural memory, highlighting the interplay between empathy, environmental justice, and representation in Lagoss floating city.
Copyright (c) 2025 Henry Chukwudi John, Diana Roig Sanz https://creativecommons.org/licenses/by-sa/4.0
Shedding Light on Loadshedding with Natural Language Processing: A social media case study on public perspectives of the South African electricity crisis in 2022
In times of collective discomfort and dissatisfaction, people often find solace in shared adversity on social media platforms like X (formerly known as Twitter). These platforms offer a unique window into the public’s emotions andviewpoints concerning common challenges. I n2022, South Africa experienced an electricity crisis, during which the country was subjectedto rolling blackouts, commonly known as load-shedding, by Eskom, the country’s primary electricity provider, to prevent a national electricity grid shutdown. This study conducted adata-driven exploration of the public discourse surrounding Eskom and loadshedding on X using natural language processing and data science techniques. The dataset utilised for thisstudy comprised tweets containing keywords related to Eskom and loadshedding. The studydelved into the topics of discussion by applying topic modelling techniques to uncover latent themes within the discourse. The topics were analysed through a multifaceted lens to unpack and highlight patterns within the sentiments, emotions and biases that underpin conversations related to loadshedding and Eskom. A notable inclusion in the analysis was the incorporation of sarcasm classifications,which enhanced the interpretation of the emotion and sentiment within the topics discussed.The findings uncovered from the analysis were contrasted with loadshedding-related events in 2022 to understand the public discourse as the electricity crisis escalated. The methodologyof this study provides a framework for utilising natural language processing techniques touncover and examine the perspectives of a collective within discourse related to events of shared interest.
Copyright (c) 2025 Avashlin Moodley, Privolin Naidoo https://creativecommons.org/licenses/by-sa/4.0
Exploring African Digital Humanities Using the Journal of the Digital Humanities Association of Southern Africa
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.
Copyright (c) 2025 Johannes Sibeko https://creativecommons.org/licenses/by-sa/4.0
Acceptance of synthetic speech in South African languages: A comparative study of Afrikaans, isiZulu, and Sepedi in healthcare contexts
While text-to-speech technologies have made significant advances in recent years, questions remain about how synthesised speech is accepted in culturally and linguistically diverse settings such as South Africa. This study explores how South Africans perceive synthetic speech in comparison to human-recorded speech across three official languages: Afrikaans, isiZulu, and Sepedi, with healthcare as the application context. Using a blind and randomised listening test, 65 participants rated audio prompts across four acceptance metrics: trust, knowledgeability, lik ability, and relatability. Statistical analysis using the Wilcoxon signed-rank test revealed no significant difference between natural and syn thesised speech perception among Afrikaans speakers. However, low participation rates prevented meaningful analysis of speech percep tion for isiZulu and Sepedi speakers. When combining data from all participants, a medium effect size favouring natural speech was ob served, though this difference was not statistically significant. These findings suggest that synthetic speech adapted from natural recordings may be suit able for certain applications in South Africa, though larger and more linguistically represen tative samples are needed to confirm these results.
Copyright (c) 2025 Johannes Abraham Louw, Ilana Wilken https://creativecommons.org/licenses/by-sa/4.0
Setting the Stage: Enabling Spaces for Dialogues with Ibali Digital Collections UCT
In 2021, the Digital Scholarship Services (DSS -formerly Digital Library Services) department at University of Cape Town Libraries launched a university-wide showcasing platform for the university’s digital collections: https://ibali.uct.ac.za. The site is called Ibali (Xhosa for ‘story’), and it runs on a set of semantic web technologies called Omeka S and IIIF. Ibali is part of UCT Libraries’ drive to nurture an Open Access space where digital collections can be created, curated, published, and showcased. It is a highly collaborative and flexible, future-thinking online repository space that supports Digital Humanities projects. Since its launch, Ibali has hosted a range of diverse sites, including heritage and community resources on endangered South African languages, a video archive for a theatrical research project, repeat landscape photography database, student-led curations, and selected library collections. The main architecture of Ibali is the open-source software Omeka S. Omeka S is a web publishing platform for GLAMs (Galleries | Libraries | Archives | Museums), designed to create relationships between objects in collections as well as describe them through linked open data resources on the internet. The ‘S’ in Omeka S stands for ‘semantic’, as in connecting to the semantic web, where data in web pages is structured and tagged. Its primary focus is on organising elements of a collection such that the links in between items and the greater elements of the internet are strengthened, allowing for much more relevant searches and deeper explorations. However, what Omeka S also allows, through the many modules developed by its growing open-source community, is the building of interactions between its showcase sites, creators and visitors. The incorporation of semantic technologies within metadata allows the conversations and feedback to be incorporated into the actual showcase site itself, enhancing archives and allowing for multiple voices to emerge and the possibility of many different interpretations of collections. The digital showcase space becomes a stage for stories, embracing the transactional, transformative, and migratory nature of images, events, recordings of our archives and our collective memories. This paper outlines the Ibali approach to building collection showcase sites that aim to foster dialogue and participation. I weave this together with the opportunities that the metadata infrastructure of Omeka S provides for sharing not only stories but diverse perspectives. Marking five years since its launch, I also briefly reflect on challenges and opportunities related to sustainability and touch upon the impact of AI on the platform and workflows.
Copyright (c) 2025 Sanjin Muftic https://creativecommons.org/licenses/by-sa/4.0
Artificial Intelligence: A New Global System, a Genocidal Project or the revival of the tokoloshe culture?
In the context of inclusive innovation, artificial intelligence (AI), presents opportunities to address inequality and social exclusion by integrating fairness, inclusivity, and representation. Despite AI's advantages, such as being a transformative force in the global landscape, affecting our traditional labour systems, and becoming a part of our daily lives. It is important to consider the potential downsides, including deepening inequalities and enhancing the digital divide. This article explores the multifaceted nature of AI, examining whether it implies developing a new global system, risks becoming a “genocidal project”, or challenging traditional African ways of being. We illustrate this by comparing AI usage and African Epistemologies to understand how both have a dual nature in their adaptability and versatility in shaping our everyday lives. Using the African Epistemological lenses of ubuntu and African folklore of the tokoloshe, we incorporate evidence from academic sources and policy, we argue that AI's replacement of human labour is a form of economic genocide, mainly impacting less advantaged people by intensifying inequalities and unemployment. This paper aims to contribute to the growing study of Inclusive Innovation by incorporating AI and African experiences; emphasising the philosophy of ubuntu by bringing to the fore humanness in the development of AI in Southern Africa. We offer policy recommendations for policy development that emphasise the challenges and influence of AI’s potential for inclusive innovation. These recommendations promote equitable access to technology and prioritise ethical considerations to avoid harm and marginalisation.
Artificial intelligence, Inclusive Innovation, African epistemology, Capitalism, Traditional Labour.
Copyright (c) 2025 Lebogang Khoza, Zikhona Necolette Ngqula https://creativecommons.org/licenses/by-sa/4.0
An empirical content analysis of posts made to the r/depression subreddit
Online fora are one of the oldest spaces for internet communication. These fora provide internet users the opportunity to connect with others of similar interests and experiences. Online mental health communities are fora for individuals that wish to connect with others based on a shared mental health experience. These digital ecosystems offer an avenue for seeking advice or validation, as well as for freely sharing experiences with similar others within a culture of reduced stigma and social support. Reddit is a popular and readily accessible platform that hosts moderated communities known as subreddits, which include communities for mental health concerns such as depression, anxiety, trauma and eating disorders. This study is an analysis of data collected by way of the Reddit application programming interface (API) from the r/depression subreddit. A conceptual framework was developed for preparing and evaluating the data by way of an empirical content analysis. The content analysis was conducted on 11975 posts made by 9593 unique user accounts over a 56-day period. The analysis of user behaviour in this subreddit relates to general engagement, the temporal attributes of the dataset, and the demographic and geographic attributes of the users. This investigation provides insights into the words most frequently used in posts made to this subreddit, the time of day and day of the week that most individuals posted to the forum, the age and locational distribution of r/depression subreddit users accounted for in the dataset and how these insights relate to the global prevalence of depression.
Copyright (c) 2024 Kurt Marais https://creativecommons.org/licenses/by-sa/4.0
Decoding Southern African Folktales using Hylistic Analysis
In this submission, the potential of hylistic analysis for the domain of Southern African folklore is demonstrated. For that purpose, narrative sequences of folktales are carefully re-constructed according to the new hylistic theory and analysed on a subset of 30 folktales from Henry Callaway's Nursery Tales and Histories of the Zulus, a unique parallel resource in English-vernacular isiZulu. The dataset, consisting of 5176 distinct narrative statements, so-called hylemes in 384 narrative sequences, is presented as a freely accessible resource which holds transformative potential for the re-interpretation and (automatic) processing of folktale narratives. It is the first step towards a thorough investigation of Callaway's collection, and an effort to the analysis of the tales' narrative structures. The dataset can be used as a resource for many future studies on folktale characters and plots as well as the study of historical isiZulu.
Copyright (c) 2025 Franziska Pannach https://creativecommons.org/licenses/by-sa/4.0