Datasets from the RecSys 2023 article "Ex2Vec: Characterizing Users and Items from the Mere Exposure Effect".

<p>We have publicly released the anonymized &quot;new_release_stream.csv&quot;&nbsp;dataset from the music streaming platform Deezer. This dataset is described in detail in the article titled &quot;Ex2Vec: Characterizing Users and Items from the Mere Exposure Effect&quot;,&nbsp;which was published in the proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023).</p> <p>Each row in the dataset contains an anonymized user and item identifier, a reference timestamp in seconds (measured from the first consumption in the dataset), and a binary value &quot;y&quot;.&nbsp;This &quot;y&quot;&nbsp;value indicates whether a song was listened to for more than 80% of its duration (y = 1) or not (y = 0).</p> <p>You can find this dataset in the GitHub repository <a href="https://github.com/deezer/ex2vec">deezer/ex2vec</a>,&nbsp;where it is used to reproduce experiments discussed in the article.</p> <p>If you plan to use our code or data in your work, please make sure to cite our paper accordingly.</p> <p>&nbsp;</p> <pre><code>@inproceedings{sguerra2023ex2vec, title={Ex2Vec: Characterizing Users and Items from the Mere Exposure Effect}, author={Sguerra, Bruno and Tran, Viet-Anh and Hennequin, Romain}, booktitle = {Proceedings of the 17th ACM Conference on Recommender Systems}, year = {2023} }</code></pre> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>