Authors:
Iaakov Exman
;
Asaf Yosef
and
Omer Ganon
Affiliation:
Software Engineering Department, The Jerusalem College of Engineering – JCE - Azrieli, Jerusalem, Israel
Keyword(s):
Weak Ties, Surprise, Relevance, Knowledge Discovery, Social Network, Automatic Luck Generation, Keyword Clouds, Keyword Frequencies, Semantic Distance, Topology, Target Task, Customer, Followers.
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 gr
aphs calculated for specific customers.
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