8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Global and country-specific mainstreaminess measures: Definitions, analysis, and usage for improving personalized music recommendation systems

      Preprint
      ,

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Popularity-based approaches are widely adopted in music recommendation systems, both in industry and research. However, as the popularity distribution of music items typically is a long-tail distribution, popularity-based approaches to music recommendation fall short in satisfying listeners that have specialized music. The contribution of this article is three-fold. We provide several quantitative measures describing the proximity of a user's music preference to the music mainstream. We define the measures at two levels: relating a listener's music preferences to the global music preferences of all users, or relating them to music preferences of the user's country. Moreover, we adopt a distribution-based and a rank-based approach as means to decrease bias towards the head of the long-tail distribution. We analyze differences between countries in terms of their level of mainstreaminess, uncover both positive and negative outliers (substantially higher and lower country-specific popularity, respectively, compared to the global mainstream), and investigate differences between countries in terms of listening preferences related to popular music artists. We use the standardized LFM-1b dataset, from which we analyze about 8 million listening events shared by about 53,000 users (from 47 countries) of the music streaming platform Last.fm. We show that there are substantial country-specific differences in listeners' music consumption behavior with respect to the most popular artists listened to. We conduct rating prediction experiments in which we tailor recommendations to a user's level of preference for the music mainstream using the proposed 6 mainstreaminess measures. Results suggest that, in terms of rating prediction accuracy, each of the presented mainstreaminess definitions has its merits.

          Related collections

          Author and article information

          Journal
          14 December 2019
          Article
          10.1371/journal.pone.0217389
          1912.06933
          96dde1f1-bdfe-4200-8354-a276da840d9e

          http://creativecommons.org/licenses/by/4.0/

          History
          Custom metadata
          PLOS ONE 2019, 14(6), Art no. e0217389
          36 pages, 4 figures, 10 tables, PLOS ONE 14(6), paper e0217389
          cs.IR cs.SI

          Social & Information networks,Information & Library science
          Social & Information networks, Information & Library science

          Comments

          Comment on this article