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Faculty & Research


Diffusion of Competing Rumours on Social Media

Award Winning
Journal Article
This paper investigates the dynamics of communication on social media, related to the spread of rumours, by studying the impact of micro-level agent interactions within social media discussions, on macro-level outcomes related to the diffusion of rumours. An agent-based framework is used to model social media discussions, modularly describing heterogeneous agents with differentiating characteristics, their interaction dynamics, rumour state transitions, and the evolution of networks on which these agents interact. Studying the effect of population, agent, interaction, and network characteristics, the authors find that some unobservable characteristics, like the initial distribution of opinions, play a significant role in rumour outcomes, particularly the homogeneity and polarisation of opinions. The authors report their findings on the mechanism and interactions and suggest heuristics for managers to counter the spread of unfavourable rumours.

Professor of Operations Management

Professor of Technology and Operations Management