Discovery of unusual regional social activities using geo-tagged microblogs

The advent of microblogging services represented by Twitter evidently stirred a popular trend of personal update sharing from all over the world. Furthermore, the recent mobile device and wireless network technologies are greatly expanding the connectivity between people over the social networking sites. Regarding the shared buzzes over the sites as a crowd-sourced database reflecting a various kind of real-world events, we are able to conduct a variety of social analytics using the crowd power in much easier ways. In this paper, we propose a geo-social event detection method by finding out unusually crowded places based on the conception of social networking sites as a social event detector. In order to detect unusual statuses of a region, we previously construct geographical regularities deduced from geo-tagged microblogs. Especially, we utilize a large number of geo-tagged Twitter messages which are collected by means of our own tweets acquisition method in terms of geographic relevancy. By comparing to those regularities, we decide if there are any unusual events happening in monitoring geographical areas. Finally, we describe the experimental results to evaluate the proposed unusuality detection method on the basis of geographical regularities which are computed from a large number of real geo-tagged tweet dataset around Japan.