Dataset Open Access

LFM-BeyMS

Peter Müllner; Dominik Kowald; Markus Schedl; Christine Bauer; Eva Zangerle; Elisabeth Lex


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3784765", 
  "author": [
    {
      "family": "Peter M\u00fcllner"
    }, 
    {
      "family": "Dominik Kowald"
    }, 
    {
      "family": "Markus Schedl"
    }, 
    {
      "family": "Christine Bauer"
    }, 
    {
      "family": "Eva Zangerle"
    }, 
    {
      "family": "Elisabeth Lex"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2020, 
        5, 
        5
      ]
    ]
  }, 
  "abstract": "<p>This dataset is based on the LFM-1b [1] and the Cultural LFM-1b [2] datasets. LFM-BeyMS includes equally-sized groups of both, beyond-mainstream and mainstream music listeners and thus, can be used for studying the characteristics of beyond-mainstream music listeners for recommendation experiments.&nbsp;For more details, we refer to our publication in <a href=\"https://arxiv.org/abs/2102.12188\">https://arxiv.org/abs/2102.12188</a>.</p>\n\n<p>LFM-BeyMS contains<br>\n* 4,148 users<br>\n* 1,084,922 tracks<br>\n* 110,898 artists<br>\n* 16,687,363 listening events</p>\n\n<p>The python code utilized for generating and exhaustively analyzing this dataset&nbsp;can be found in&nbsp;<a href=\"https://github.com/pmuellner/supporttheunderground\">https://github.com/pmuellner/supporttheunderground</a>.</p>", 
  "title": "LFM-BeyMS", 
  "type": "dataset", 
  "id": "3784765"
}
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