LastFM Asia Social Network and Music Listening Data

A social network graph from LastFM users in Asia, capturing user connections and music listening habits. The dataset originates from the UCI Machine Learning Repository, a known source for benchmark datasets. Specific temporal coverage and collection details are not provided in the available metadata.

Use Cases

• Analyze community structure and clustering coefficients within the Asian LastFM user graph to identify music taste communities.
• Apply link prediction algorithms using user node features and existing edge connections to forecast new friendships.
• Study the correlation between network centrality metrics (like degree or betweenness) and user listening behavior features.
• Benchmark graph neural network models for node classification tasks, such as predicting user demographics from network position and music genre preferences.

Strengths

• Dataset is hosted by the UCI Machine Learning Repository, ensuring stable access and versioning.
• Represents real-world social network and user behavior data from a major music platform.

Limitations

• Unknown number of nodes (users) and edges (connections), making it difficult to assess scale.
• Lack of column names or sample data prevents detailed understanding of available features.
• Geographic scope is limited to Asia, which may limit generalizability of findings.

Provenance

Source

UCI Machine Learning Repository

Collection Method

Collected from the Last.fm online music service, likely via API.

Geography

Asia