Understanding the Spread of Social Influence Using Social Network Analysis and Agent-Based Modeling

Abstract

Knowledge of the flow of social influence is essential to effectively analyzing social media in postmodern societies. This research examined how social influence diffused in the Pakistani context by employing SNA and ABM. Data regarding social connections, influence, and interaction was collected by surveying a purposive sample of 475 active social media users randomly connecting urban and rural parts of Pakistan. SNA disclosed other centrality measurements, showing how people with connectivity or reputation within the network enhanced the flow of influence. The structural characteristics of the networks under consideration (scale-free, small-world, and random), as well as the vulnerability of an individual node in the network, are influenced by the ABM simulations for the velocity and range of influence diffusion. The result of the analysis showed that the influence spread happened much faster in the urban region than in the rural region. The research finds that understanding network centrality and individual vulnerability can help build an effective approach to disseminating influence. Recommendations involve identifying opinion leaders, exploiting structure, and targeting targeted nodes for increased influence in different regions of susceptibility.