Browsing by Author "Bagui, Laban"

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    Open Access
    An analytical tale of the social media discursive enactment of networked everyday resistance during the #feesmustfall social movement in South Africa
    (2019) Bagui, Laban; Johnston, Kevin; Weimann, Peter
    Social media are a space for discussions, debates and deliberations about personality, culture, society, and actual experiences of social actors in South Africa. They offer an unexpected opportunity for the broader consideration and inclusion of community members’ voices in governance decision making and policy processes. They also offer opportunities to engage, mobilise and change people and society in impressive scale, speed and effect: They have mobilising and transformative powers emanating from their interaction with the impetus of the agency of community members seeking better conditions of living. The magnitude of the effects of these powers makes it imperative to have a better understanding of their workings. Social media have been used in numerous social movements as the medium of communication to mobilise, coordinate, and broadcast protests. However, social media were never a guarantee of success as most movements using them did not achieve significant results. Yet, governments in developed and developing countries tend to engage inadequately with social media supported movements. The research problem is that the contribution of social media to the transformation of the social practice of discourse, which causes SSA community members’ agential impetus (collective intentionality for action) to generate a discourse of resistance on social media during social movements, is not well understood. The main research question is: Why are South African community members using social media to enact online discursive resistance during social movements? The aim of the research is to explain, from a critical realism point of view, Sub-Saharan African community members’ emergent usage of social media during social movements, by providing a contextualised social history (a tale) of South African community members’ practice of online discursive enactment of resistance. The emergent usage of social media of concern is conceptualised as “discursive enactment of networked everyday resistance” within a dialectical space of interaction conceptualised as “space of autonomous resistance”; an instance of a communication space allowing for transformative negation to occur. The research follows Bhaskar’s Critical Realism as a philosophical paradigm. Critical Realism seeks to explain phenomena by retroducing (retrospective inference) causal explanations from empirically observable phenomena to the generative mechanisms which caused them. The research was designed as a qualitative, processual and retroductive inquiry based on the Morphogenetic/Morphostasis approach with two phases: an empirical research developing the case of South African community members’ emergent usage of social media during the #feesmustfall social movement, looking for demi-regularities in social media discourse; and a transcendental research reaching into the past to identified significant events, objects and entities which tendencies are responsible for the shape of observed discourse. In the first phase, a case study was developed from data collected on the social media platform Twitter™, documents, and in-depth interviews of South African community members. The data collected were analysed using qualitative content analysis (QCA) and Critical Discourse Analysis (CDA) to unveil demi-regularities; moving from the observable individual strategic orientation of messages to discourses, thus to the tendencies of relational emergent properties of systemic magnitude which structure local discourses and are transformed by them. Then, the social mediainduced morphogenesis or transformation of South African community members’ discursive action was postulated in an analytical history of emergence (or analytical tale) of their usage of social media within a “space of autonomous resistance” during social movements. The findings of the research suggest that South African community members authored 3 discourses of resistance on Twitter™: #feesmustfall discourses of struggle, identity and oppression. They identified as “student qua black-child” stepping into the “Freedom fighter” role against the hegemonic post-apartheid condition curtailing their aspirations. It was found that social media socio-cultural embeddedness and under-design (Western European socio-cultural globalising underpinning features and functional features of the platforms) which interaction with the local socio-cultural mix (postapartheid socio-cultural tendencies for domination/power, spiral of silence, and legitimacy/identification) resulted in misfits and workarounds enhancing individual emotional conflict and aligning towards a socio-cultural opportunistic contingent complementarity integration in the deployment of discourse. That integration was actualised as a mediatization emergent property through asignification/signification of mainstream discourses of liberal democracy, colonial capitalism, national democratic revolution, free and decolonised education, black consciousness and Fallism. That mediatization through re-signification of the struggle for freedom created a communication “space of autonomous resistance” where networked freedom fighters enacted discursive everyday resistance against the hegemonic forces of students’ precariousness. The contribution of the research includes a realist model of social media discursive action (ReMDA); an explanation of South African community members’ deployment of discourse over social media during social movement and telling the tale of the transformation of discursive practices with the advent of social media in South Africa.
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    Open Access
    The use of artificial intelligence for business optimisation in banking: case of Nigeria
    (2025) Akobe, David; Chigona, Wallace; Bagui, Laban
    Background: The continuous increase in the amount of customer data stored by commercial banks necessitates the use of artificial intelligence (AI) technologies. AI technologies may be used for analysing customer data and predicting customer behaviour, with the aim of customer retention and satisfaction. Such technologies include machine learning algorithms and deep learning models. Commercial banks in Nigeria are employing these predictive analysis tools. However, not all Nigerian commercial banks currently use them. Objective: The objective of this study is to explore how Nigerian commercial banks use AI technologies for business optimisation. Methodology: This study was interpretivist, abductive, and followed a qualitative approach deploying a multiple case study design. This study used the Organisational information processing (OIP) theory as a theoretical framework. Through the concept of matching information processing capabilities to information processing needs, the study explored the use of AI in Nigerian commercial banks. The multiple case study design consisted of three banks, selected from a total of nineteen commercial banks. A purposive sampling approach was used to select 20 experienced data professionals from business intelligence (BI) departments of the selected banks. Data was collected through semi-structured interviews. The study used thematic analysis to analyse the data. Findings: Findings show that information processing needs such as customer and data needs motivated commercial banks to utilise AI technologies as information processing capabilities. AI technologies such as the Sentiment intensity analyser, LR, K-means algorithm, Naïve Bayes algorithm, K-nearest neighbour, and Recommendation engines, were used for various tasks. For example, sentiment analysis, customer segmentation, customer churn prediction, predicting loan collection credibility and product recommendations. Findings also show that deep learning models were not used by the commercial banks, due in part to a lack of computational resources Contribution: The research confirmed that the use of AI in commercial banks in Nigeria contributes to customer retention and satisfaction. It provided knowledge of how AI technologies were used by commercial banks. This knowledge is important for other banks in Nigeria that may eventually use AI technologies due to the constant growth of customer data. The study also refined the organisational information processing theory to capture the findings. The refined version was titled ‘Nigerian Commercial Bank Information Processing View'.