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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. For more details, we refer to our publication in https://arxiv.org/abs/2102.12188. LFM-BeyMS contains * 4,148 users * 1,084,922 tracks * 110,898 artists * 16,687,363 listening events The python code utilized for generating and exhaustively analyzing this dataset can be found in https://github.com/pmuellner/supporttheunderground.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 37 |

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