Abstract
One often thinks that the use of Information Technologies brings an infinity of choices. However, Popularity still influences people in our free, pervasive and connected world. It is a reality: popular items keep power and weak items tend to be forgotten. Several studies demonstrated that this natural phenomenon is accentuated today with recommender engines. In this article we present a comparative study of 8 recommendation techniques. We also present a personal recommendation approach, based on items timeline. We unveil a Popularity Influence index, which evaluates the way recommender engines are influenced by the phenomenon. This experiment is led by a pool of interdisciplinary researchers, either or both epistemologists and computer scientists. It includes diverse examples and references from e-business, cultural studies or participatory democracy along with others. We believe that Popularity belongs to a wide set of fields. Therefore, we chose to run this experiment in an E-learning context, where we observe pieces of knowledge popularity.
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Blot, G., Saurel, P., Rousseaux, F. (2015). Recommender Engines Under the Influence of Popularity. In: Benyoucef, M., Weiss, M., Mili, H. (eds) E-Technologies. MCETECH 2015. Lecture Notes in Business Information Processing, vol 209. Springer, Cham. https://doi.org/10.1007/978-3-319-17957-5_9
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