Dataset Open Access
Eva Zangerle;
Asmita Poddar;
Yi-Hsuan Yang
The nowplaying-rs dataset features context- and content features of listening events. It contains 11.6 million music listening events of 139K users and 346K tracks collected from Twitter. The dataset comes with a rich set of item content features and user context features, as well as timestamps of the listening events. Moreover, some of the user context features imply the cultural origin of the users, and some others - like hashtags - give clues to the emotional state of a user underlying a listening event.
The dataset contains three files:
Please note that user_track_hashtag_timestamp.csv and context_content_features.csv partly provide the same features. We deliberately chose to do so to be able to provide useable files that do not have to be matched and joined with each other to perform e.g., simple recommendation tasks.
Please also find the training and test-splits for the dataset in this repo. Also, Asmita provides prototypical implementations of a context-aware recommender system based on the dataset at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM.
If you make use of this dataset, please cite the following paper where we describe and experiment with the dataset:
@inproceedings{smc18,
title = {#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems},
author = {Asmita Poddar and Eva Zangerle and Yi-Hsuan Yang},
url = {http://mac.citi.sinica.edu.tw/~yang/pub/poddar18smc.pdf},
year = {2018},
date = {2018-07-04},
booktitle = {Proceedings of the 15th Sound & Music Computing Conference},
address = {Limassol, Cyprus},
note = {code at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM},
tppubtype = {inproceedings}
}
Name | Size | |
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nowplaying_rs_train_test.zip
md5:32d00b55dbeb2b617fd041c8156d3e86 |
27.0 MB | Download |
nowplayingrs.zip
md5:b2fc636fbd3ea8ddf81165aab197108a |
2.7 GB | Download |
Poddar, Asmita; Zangerle, Eva; Yang, Yi-Hsuan #nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems Inproceedings Proceedings of the 15th Sound & Music Computing Conference, Limassol, Cyprus, 2018.
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