Modelling Individual Behaviour Towards Influencers on Social Media Using Cell-DEVS

Abstract

With the exponentially rising popularity of social media, and the provided convenience of digital advertising across various platforms, individuals have found ways to sustain a lifestyle by providing companies a personalised platform for advertising their products.These individuals are popularly labelled as "influencers". Determining the impact an influencer has to a product's market is an important aspect in determining whether a company should invest in the influencer's platform. This thesis research applies and enhances previous approaches of modelling social interactions to simulate the effects of an influencer on its surrounding environment.The "influencer" model employs the Cell-DEVS formalism implemented through the Cadmium tool to simulate the reaction of individuals towards an "influencer". The "influencer" model provides means by which the effects of an influencer can be simulated under various scenarios while combining opinion and social interaction-based approaches to simulating human behaviour.This research presents a model to simulate the evolution of opinions and the resulting events regarding following or not following an influencer as a conclusion of the influenced human behaviour. The model, referred to as the 'influencer' model, is based on the methodologies presented by Behl et al [2], Wang et al [3] and White at al [4], which present simulation strategies for opinion evolution, sentiment propagation, and the spread of COVID-19, respectively. The 'influencer' model uses the Cell-DEVS formalism (an extension of the cellular automata formalism that can be used to build discrete-event cell spaces [43]), Agent-Based modelling, Network diffusion processes, and it is implemented