The bionic DBMS is coming, but what will it look like?
Ryan Johnson, Ippokratis Pandis
CIDR 2013
This work deals with the task of predicting the popularity of user-generated content. We demonstrate how the novelty of newly published content plays an important role in affecting its popularity. More specifically, we study three dimensions of novelty. The first one, termed contemporaneous novelty, models the relative novelty embedded in a new post with respect to contemporary content that was generated by others. The second type of novelty, termed self novelty, models the relative novelty with respect to the user's own contribution history. The third type of novelty, termed discussion novelty, relates to the novelty of the comments associated by readers with respect to the post content. We demonstrate the contribution of the new novelty measures to estimating blog-post popularity by predicting the number of comments expected for a fresh post. We further demonstrate how novelty based measures can be utilized for predicting the citation volume of academic papers. © 2012 ACM 2157-6904/2012/09-ART69.
Ryan Johnson, Ippokratis Pandis
CIDR 2013
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