How do we evaluate systems that filter social media streams and send users updates via push notifications on their mobile phones? Such notifications must be relevant, timely, and novel. In this paper, we explore various evaluation metrics for this task, focusing specifically on measuring relevance. We begin with an analysis of metrics deployed at the TREC 2015 Microblog evaluations. A simple change to the metrics, reflecting a different assumption, dramatically alters system rankings. Applying another metric, previously used in the TREC Microblog evaluations, again yields different system rankings. We find little correlation between a number of "reasonable" evaluation metrics, which suggests that system effectiveness depends on how you measure it---an undesirable state in IR evaluation. However, we argue that existing evaluation metrics can be generalized into a framework that uses the same underlying contingency table, but places different weights and penalties. Although we stop short of proposing the "one true metric", this framework can guide the future development of a family of metrics that more accurately models user needs.
['Luchen Tan', 'Adam Roegiest', 'Jimmy J. Lin', 'Charles L. A. Clarke']
An Exploration of Evaluation Metrics for Mobile Push Notifications