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How did Facebook grow? Did Twitter, LinkedIn, WeChat and others grow in the same way? — A Network-Based Universal Growth Law


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The growth of the user population of a newly launched product or service is often considered as being controlled by multiple factors like deployment of appropriate business strategy, quality of the product, market readiness, and luck! Recent research in network science has provided convenient access to the construction of models that can describe collective human behaviour. Here, we discuss a model, based on construction of a networked community and two fundamental behaviour of decision making, that can universally describe the growth of the user population of any newly launched product or service. This model leads to a universal growth equation that describes dynamically the size of the user population in terms of the prospective market size and the extents of peer influence and personal choice. We analyse 22 sets of realworld historical growth data of a variety of products and services, and show that they all follow the universal growth equation. The numerical procedure for finding the model parameters allows the market size, and the relative effectiveness of customer service and promotional efforts to be estimated from the available historical growth data. This model can be extended to a variety of practical growth applications. This talk will highlight the role of data, combined with the use of appropriate theory, in many areas of applied research.