Combining Spotify and Twitter Data for Generating a Recent and Public Dataset for Music Recommendation

In this paper, we present a dataset based on publicly available information. It contains listening histories of Spotify users, who posted what they are listening at the moment on the micro blogging platform Twitter. The dataset was derived using the Twitter Streaming API and is updated regularly. To show an application of this dataset, we implement and evaluate a pure collaborative ltering based recommender system. The performance of this system can be seen as a baseline approach for evaluating further, more sophisticated recommendation approaches. These approaches will be implemented and benchmarked against our baseline approach in future works

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