Ranking Approaches for Microblog Search

Abstract

Ranking microblogs, such as tweets, as search results for a query is challenging, among other things because of the sheer amount of microblogs that are being generated in real time, as well as the short length of each individual microblog. In this paper, we describe several new strategies for ranking microblogs in a real-time search engine. Evaluating these ranking strategies is non-trivial due to the lack of a publicly available ground truth validation dataset. We have therefore developed a framework to obtain such validation data, as well as evaluation measures to assess the accuracy of the proposed ranking strategies. Our experiments demonstrate that it is beneficial for microblog search engines to take into account social network properties of the authors of microblogs in addition to properties of the microblog itself.