Abstract— Review Selection Using Micro-Reviews. Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise < Final Year Projects 2016 > and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Speciﬁcally, we use coverage of micro-reviews as an objective for selecting a set of reviews that cover efﬁciently the salient aspects of an entity.