Scielo RSS <![CDATA[The African Journal of Information and Communication]]> http://www.scielo.org.za/rss.php?pid=2077-721320230001&lang=en vol. 31 num. lang. en <![CDATA[SciELO Logo]]> http://www.scielo.org.za/img/en/fbpelogp.gif http://www.scielo.org.za <![CDATA[<b>"If it is circulating widely on social media, then it is likely to be fake news": Reception of, and motivations for sharing, COVID-19-related fake news among university-educated Nigerians</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100001&lng=en&nrm=iso&tlng=en This study explores how university-educated Nigerians living in two urban centres engaged with, and made choices about whether to share or not share, "fake news" on COVID-19 in 2020. The research adopted a qualitative approach by conducting focus group interviews with participants, all university graduates aged 25 or older, sampled from Lagos and Umuahia-two major metropolitan cities in Nigeria. Participants' sense-making practices with regard to fake news on COVID-19 were varied. One core finding was that social media virality was typically seen as being synonymous with fake news due to the dramatic, exaggerated, and sometimes illogical nature of such information. Many participants demonstrated a high level of literacy in spotting fake news. Among those who said that they sometimes shared fake news on COVID-19, one motivation was to warn of the dangers of fake news by making it clear, while sharing, that the information was false. Other participants said that they shared news without being certain of its veracity, because of a general concern about the virus, and some participants shared news if it was at least partially true, provided that the news aimed to raise awareness of the dangers of COVID-19. However, some participants deliberately shared fake news on COVID-19 and did so because of a financial motivation. Those who sought to avoid sharing fake news on COVID-19 did so to avoid causing harm. The study provides insights into the reception of, and practices in engaging with, health-related fake news within a university-educated Nigerian demographic. <![CDATA[<b>Competition regulation for digital markets: The South African experience</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100002&lng=en&nrm=iso&tlng=en The study examines the recent experiences of South Africa's competition authorities in engaging with competition matters in the country's digital markets. Specifically, the authors examine engagements by the Competition Commission South Africa (CCSA), the Competition Tribunal of South Africa, and the Competition Appeal Court (CAC) with three regulatory elements: (1) mergers, examined through the MIH and WeBuyCars and Google and Fitbit cases; (2) abuse of dominance, examined through the GovChat v Facebook case; and (3) cartel conduct, examined through the Competition Commission v Bank of America Merrill Lynch International Limited & Others case. In reviewing the decisions made in these cases, the authors highlight regulatory considerations that are coming to the fore in response to competition matters in digital markets. <![CDATA[<b>COVID-19, <i>kovhidhi, dzihwamupengo: </i>Language use, language change, and pandemic perceptions among Shona-speakers in Gweru, Zimbabwe</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100003&lng=en&nrm=iso&tlng=en Through an examination of the linguistic practices encountered and used by Shona language-speakers in the Zimbabwean city of Gweru, this study explores intersections between language use, language change, and perceptions of the COVID pandemic-as caused by the virus referred to by Gweru's Shona-speakers as, variously, "COVID-19" in its English-language representation or "kovhidhi" or "dzihwamupengo" in its two most common Shona-language representations. The study is anchored in conceptions of the impacts that natural disasters and pandemics have on language and on communication needs, and in theories of semiotics and language change. The research finds that the predominant terms used by Gweru's Shona-speakers in relation to the pandemic carry connotations that, in the Zimbabwean socio-cultural context, potentially undermine optimal responses to the pandemic. The article concludes by emphasising the importance of careful management of language as a critical resource in the fight against natural disasters and pandemics. <![CDATA[<b>Factors influencing post-hackathon project continuation in an African corporate setting</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100004&lng=en&nrm=iso&tlng=en This article reports on a study examining the factors influencing post-hackathon project continuation in a company with presence in several African countries. The research was conducted as a case study, and focused on hackathon events held by the company between 2018 and 2020. The study identified three core factors that influenced the potential for project continuation after the corporate hackathons: (1) availability of financing; (2) team skills fit and diversity; and (3) degree of project integration into company operations. Where one or more of these elements was insufficiently present, then project continuation became less likely-and the likelihood of project discontinuation increased. The findings are of potential utility to corporate hackathon organisers seeking to increase the levels of project continuation-and, by, extension, return on investment-from their companies' hackathon projects. <![CDATA[<b>Evaluation of web-based online agricultural information relevant to Tanzanian maize producers</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100005&lng=en&nrm=iso&tlng=en This study examined the quality of web-based online agricultural information relevant to the maize industry in Tanzania. Selected online sources were evaluated to assess the agricultural information available in terms of four dimensions of quality, namely: authority, completeness, timeliness, and understandability. The study identified a wide variety of web-based online information on maize production, including information on seeds, fertilisers, pesticides, and grain-handling. It was found that the information was of variable quality. Among the 39 online sites studied, several lacked contact information, had outdated content, and contained information that was missing some important details, and none provided weather information. This study contributes to the body of knowledge on online agricultural information in an African context where the agricultural sector is central to national economic development. The online agriculture information evaluation tool used in the study can potentially be of use, in its current form or adapted, to researchers beyond Tanzania. <![CDATA[<b>Exploring COVID-19 public perceptions in South Africa through sentiment analysis and topic modelling of Twitter posts</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100006&lng=en&nrm=iso&tlng=en The narratives shared on social media during a health crisis such as COVID-19 reflect public perceptions of the crisis. This article provides findings from a study of the perceptions of South African citizens regarding the government's response to the COVID-19 pandemic from March to May 2020. The study analysed Twitter data from posts by government officials and the public in South Africa to measure the public's confidence in how the government was handling the pandemic. A third of the tweets dataset was labelled using valence aware dictionary and sentiment reasoner (VADER) lexicons, forming the training set for four classical machine-learning algorithms-logistic regression (LR), support vector machines (SVM), random forest (RF), and extreme gradient boosting (XGBoost)-that were employed for sentiment analysis. The effectiveness of these classifiers varied, with error rates of 17% for XGBoost, 14% for RF, and 7% for both SVM and LR. The best-performing algorithm (SVM) was subsequently used to label the remaining two-thirds of the tweet dataset. In addition, the study used, and evaluated the effectiveness of, two topic-modelling algorithms-latent dirichlet allocation (LDA) and non-negative matrix factorisation (NMF)-for classification of the most frequently occurring narratives in the Twitter data. The better-performing of these two algorithms, NMF, identified a prevalence of positive narratives in South African public sentiment towards the government's response to COVID-19. <![CDATA[<b>China's digital transformation: Data-empowered state capitalism and social governmentality</b>]]> http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S2077-72132023000100007&lng=en&nrm=iso&tlng=en The article scrutinises the trajectory of China's establishment of a digital state, rooted in a "whole-of-nation" system-or aptly termed (party-)state capitalism. The author illustrates the path of formulating and enforcing strategies to digitalise public services-including, importantly, the digital identity infrastructure-via institutional concentration that exemplifies both the positive and the exclusionary nature of social big data in streamlining administrative procedures. Two catalysts are spotlighted in China's digital transformation: quasi-neoliberal market processes, and technology's social change spillover effects. The author points to the fact that, since its inception, the contemporary Chinese state has created a cybernetic justification for "social governmentality", as a means to redress potential informational imbalances in the process of ruling the state polity. For the Chinese administrative hierarchy, data provides the means to execute a top-down correctivist paradigm for steering societal conduct, a paradigm integrated into (but also to some extent in tension with) data-empowered state capitalism.