Irena Grabovitch-Zuyev
Yaron Kanza
ABSTRACT
Microblogs allow users to publish geo-tagged posts---short textual messages assigned to a geographic location. Users send posts from places they visit and discuss an idiosyncratic mixture of personal and general topics. Thus, it is reasonable to assume that the locations and the textual content of posts will be unique and will identify the posting user, to some extent. This raises the question whether there is a correlation between the locations of posts and their content. Are users who are similar from the geospatial perspective (i.e., who send messages from nearby locations) also similar from the textual perspective (i.e., send messages with similar textual content)? Do posts with similar content have a spatial distribution similar to that of any random set of posts? We present a study that focuses on these questions. We provide statistical tests to examine the correlation between textual content and geospatial locations in tweets. We show that although there is some correlation between locations and textual content, they provide different similarity measures, and combining these two properties for identification of users by their posts outperforms methods that merely use locations or only use the textual content, for identification.
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