Weak Ties Are Surprising Everywhere

Iaakov Exman, Asaf Yosef, Omer Ganon

Abstract

Weak ties between people have been known as surprisingly effective to successfully achieve practical goals, such as getting a job. However, weak ties were often assumed to correlate with topological distance in virtual social networks. The unexpected novelty of this paper is that weak ties are surprisingly everywhere, independently of topological distance. This is shown by modelling luck with reference to a target task, as a composition of a surprise function expressing weak ties and a target relevance function expressing strong ties between people. The model enables an automatic luck generation software tool, to support target tasks mainly by the surprise function. The main result is obtained by superposing the luck model upon network topological maps of customer relationships to its followers in any chosen social network. The result is validated by surprise Keyword Clouds of customer followers and Keyword Frequencies for diverse followers. Results are illustrated by a variety of graphs calculated for specific customers.

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