عنوان انگلیسی مقاله:

Marketing impact on diffusion in social networks

ترجمه عنوان مقاله: تاثیر بازاریابی در انتشار در شبکه های اجتماعی

رشته: بازاریابی

سال انتشار: 2016

تعداد صفحات مقاله انگلیسی: 39 صفحه

منبع: الزویر و ساینس دایرکت

نوع فایل: pdf

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چکیده انگلیسی مقاله

The article proposes a way to add marketing into the standard threshold model of social networks. Within this framework, the article studies logical properties of the influence relation between sets of agents in social networks. Two different forms of this relation are considered: one for promotional marketing and the other for preventive marketing. In each case a sound and complete logical system describing properties of the influence relation is proposed. Both systems could be viewed as extensions of Armstrong’s axioms of functional dependency from the database theory.

مقدمه انگلیسی مقاله

Social Networks

In this article we study how diffusion in social networks could be affected by marketing. Diffusion happens when a product or a social norm is initially adopted by a small group of agents who later influence their peers to adopt the same product. The peers influence their peers, and so on. There are two most commonly used models of diffusion: the cascading model and the threshold model. In the cascading model [18, 12] the behaviour of agents is random and the peer influence manifests itself in a change of a probability of an agent to adopt the product. In the threshold model [24, 14, 11, 1], originally introduced by Granovetter [10] and Schelling [19], the behavior ofthe agents is deterministic. Other models of diffusion, such as propositional opinion diffusion model [9], have also been studied.

نتیجه گیری انگلیسی مقاله

In this article we have suggested a way of adding marketing to the standard threshold model of diffusion in social networks. The model is general enough to simulate both promotional and preventive marketing. We have also defined formal logical systems for reasoning about influence relation in social networks with marketing of these two types. Both systems are based on Armstrong’s axioms from the database theory. The main technical results of the article are the completeness theorems for these two systems.

As a possible extension of this work, marketing could be added to other logical systems for social networks mentioned in the introduction. Another possible extension of this work is an analysis of the computational complexity of both the proposed model and the logical system. However, this would probably require switching from the real numbers to the rational numbers since the real numbers, generally speaking, can not be given as an input to a Turing machine.

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