  Twitter is an extremely popular social networking platform. Most Twitter
users do not disclose their locations due to privacy concerns. Although
inferring the location of an individual Twitter user has been extensively
studied, it is still missing to effectively find the majority of the users in a
specific geographical area without scanning the whole Twittersphere, and
obtaining these users will result in both positive and negative significance.
In this paper, we propose LocInfer, a novel and lightweight system to tackle
this problem. LocInfer explores the fact that user communications in Twitter
exhibit strong geographic locality, which we validate through large-scale
datasets. Based on the experiments from four representative metropolitan areas
in U.S., LocInfer can discover on average 86.6% of the users with 73.2%
accuracy in each area by only checking a small set of candidate users. We also
present a countermeasure to the users highly sensitive to location privacy and
show its efficacy by simulations.
