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Systèmes de recommandation et réseaux sociaux, quelles implications pour le marketing digital ?

Author

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  • Maria Mercanti-Guérin

    (DICEN-IDF - Dispositifs d'Information et de Communication à l'Ère du Numérique - Paris Île-de-France - UPN - Université Paris Nanterre - CNAM - Conservatoire National des Arts et Métiers [CNAM] - UPEM - Université Paris-Est Marne-la-Vallée)

Abstract

Les systèmes de recommandation sont pratiqués depuis l'origine par les réseaux sociaux. Le cas le plus emblématique est celui de Facebook qui intègre au fil d'actualité les préférences des amis de l'utilisateur. Au graphe social, les réseaux sociaux les plus connus ajoutent les graphes socio-géolocalisés (graph search de Facebook). L'ensemble de ces systèmes de recommandation fait l'objet de constructions d'offres publicitaires monétisées. S'ils sont incontournables pour les modèles économiques des réseaux comme Google Plus, YouTube, Twitter ou Facebook, ils soulèvent, néanmoins, un certain nombre de questions sur l'évolution du marketing digital et plus spécifiquement du e-commerce . Par ailleurs, ils ne représentent qu'un type de recommandation et se retrouvent, de plus en plus, appliqués en synergie avec d'autres types de recommandations dont la recommandation personnalisée. L'objectif de ce chapitre est donc de décrire, dans un premier temps, le concept de recommandation sociale. Nous montrerons que sa gestion est difficile pour les marques et que les systèmes de recommandation permettent de s'affranchir d'un certain nombre de difficultés portant, notamment, sur l'émetteur de la recommandation (consommateur, expert, leader d'opinion...). Dans un deuxième temps, nous mettrons en exergue les apports de ces systèmes de recommandation sur la croissance du commerce social. Nous traiterons de leur efficacité en termes de ventes en ligne, leurs principes de fonctionnement, leurs principales utilisations. Une présentation de la recommandation sociale telle qu'elle est appliquée par Facebook nous permettra d'aborder son acceptation par les consommateurs et des questionnements plus théoriques destinés à faire avancer la réflexion sur les bonnes pratiques de la recommandation sociale ainsi que les évolutions technologiques qui accroissent considérablement ses possibilités.

Suggested Citation

  • Maria Mercanti-Guérin, 2014. "Systèmes de recommandation et réseaux sociaux, quelles implications pour le marketing digital ?," Post-Print hal-02055196, HAL.
    • Handle: RePEc:hal:journl:hal-02055196
    Note: View the original document on HAL open archive server: https://hal.science/hal-02055196
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    References listed on IDEAS

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    1. Fabrice Larceneux, 2007. "Buzz et recommandation sur internet : quels effets sur le box office ?," Post-Print halshs-00660075, HAL.
    2. Herr, Paul M & Kardes, Frank R & Kim, John, 1991. "Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(4), pages 454-462, March.
    3. Eric Vernette & Laurent Bertrandias & Jean-Philippe Galan & A. Vignolles, 2012. "Construit et concept de leader d'opinion dans les réseaux sociaux : proposition d'un agenda de recherche," Post-Print halshs-00742262, HAL.
    4. Kyeongheui Kim & Meng Zhang & Xiuping Li, 2008. "Effects of Temporal and Social Distance on Consumer Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(4), pages 706-713, August.
    5. repec:dau:papers:123456789/8140 is not listed on IDEAS
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