Fang Wu and Bernardo A. Huberman
HP Laboratories
Palo Alto, CA 94304
January 23, 2008
Abstract
We analyze the role that popularity and novelty play in attracting
the attention of users to dynamic websites. We do so by determining
the performance of three different strategies that can be utilized to
maximize attention. The first one prioritizes novelty while the second
emphasizes popularity. A third strategy looks myopically into
the future and prioritizes stories that are expected to generate the
most clicks within the next few minutes. We show that the first two
strategies should be selected on the basis of the rate of novelty decay,
while the third strategy performs sub-optimally in most cases. We also
demonstrate that the relative performance of the first two strategies
as a function of the rate of novelty decay changes abruptly around a
critical value, resembling a phase transition in the physical world.
J. Basilico, and T. Hofmann. ICML '04: Proceedings of the twenty-first international conference on Machine learning, page 9. New York, NY, USA, ACM, (2004)