Recommender Systems and Social Networks: What Are the Implications for Digital Marketing?

Maria Mercanti-Guérin ()
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Maria Mercanti-Guérin: IAE Paris - Sorbonne Business School

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Abstract: Recommender Systems and Social Networks: What Are the Implications for Digital Marketing? Recommender systems have been used from the start by social networks. The most representative case is that of Facebook which currently integrates the preferences of the users' friends. The better known social networks add socio-geo-location-based graphs to the social graph (see Facebook's "graph search"). The set of these recommender systems are responsible for the creation of monetized advertising offers. Although they are vital to the economic models of networks such as Google Plus, YouTube, Twitter or Facebook, they raise a certain number of questions regarding the evolution of digital marketing and more specifically e-commerce. Furthermore, they represent only one type of recommendation and are being used increasingly in tandem with other types of recommendations including personalized recommendations. The aim of this chapter is therefore to describe, first, the concept of social recommendation. We will show that its management is difficult for brands and that recommender systems help free them from a certain number of problems concerning, notably, the transmitter of the recommendation (consumer, expert, opinion leader, etc.). Second, we will point out the benefits of these recommender systems for the development of social commerce. We will measure their efficiency in terms of online sales

Keywords: Recommeder; system (search for similar items in EconPapers)
Date: 2014-12-05
Note: View the original document on HAL open archive server: https://hal.science/hal-03124513
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Published in Recommender Systems, Wiley, pp.53-69, 2014, 9781848217683

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03124513

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