Statistical Models of Music-listening Sessions in Social Media

author: Elena Zheleva, Department of Computer Science, University of Illinois at Chicago
published: May 18, 2010,   recorded: April 2010,   views: 3891


Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography


User experience in social media is characterized by rich interaction with the media content and other participants within the online community. We use statistical models to describe the patterns of music listening in online communities at different levels of model complexity. First, we adapt the LDA model to capture the users’ taste in songs and identify the corresponding clusters of media and users. Second, we define a graphical model that takes into consideration the listening sessions and captures the listening mood of users. Our session model yields clusters of media and users that capture the behavior exhibited across listening sessions, and it allows faster inference when compared to the LDA model. Our experiments with the data from an online media site (Zune Social music community) demonstrate that the session model is better in terms of the perplexity on the music genre co-occurrence compared to the LDA-based taste model that does not incorporate cross-session information and a baseline model that does not use latent clusters.

See Also:

Download slides icon Download slides: www2010_zheleva_smm_01.pdf (908.8 KB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: