Category: A1; Team name: GAAIMC; Dataset: Deezer Europe (MUSAE)

[ixime]

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Description

This PR adds the Deezer Europe (MUSAE) dataset published in [1] for TAG-DS Topological deep learning Challenge 2025: Expanding the Data Landscape.

This dataset is a social network of Deezer users which was collected from the public API in March 2020. Nodes are Deezer users from European countries and edges are mutual follower relationships between them. The vertex features are extracted based on the artists liked by the users. The task related to the graph is binary node classification - one has to predict the gender of users. This target feature was derived from the name field for each user. [2]

This dataset was shared in PyG [3], but the url to download it is broken, so we downloaded it from [2]. In [1] the features were truncated to a dimensionality of 128 using SVD. We added the dimensionality reduction as a data transformation and is performed as default for this dataset, however the complete data is kept, in case of choosing another kind of data transformation.

The same data transformation is used in PR's #214, #216, and #217

References:

[1] B. Rozemberczki and R. Sarkar. Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models. 2020.
[2] SNAP: Network datasets_ Deezer Europe
[3] Deezer Europe in PyG

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