Implementation of a Realtime Event-location Analyzer

Abstract

A Social Networking Service (SNS) is a web-based platform that helps to build or to keep relationships among people. The SNS platforms in early stage including Friendster and MySpace were implemented for the desktop and laptop users. As more people access wireless internet using their mobile phones, SNS platforms can also have some important features such as “real-time access” and “location information”. These two features make it possible to let people share their activities, interests, and observations in real-time at any places. Recently, most of SNS platforms including Twitter, Facebook, and Yelp use the location information of users. Therefore, if we consider a SNS user as a sensor that reports its observations at a specific location, it would be possible to detect events by analyzing their social contents. There are already numbers of research on this topic have been published or still ongoing. Twitter has been widely used for conducting the research because it has important three features which are required to detect an event: time, location, and content. However, the most approaches struggle with detecting the location which is related to an event correctly. In this paper, we introduce a system that detects an event with its location in real-time based on increment of tweets that mention a specific location frequently. The result of performance evaluation shows that the proposed system detects an event in real-time. We also improved the system performance by reducing some noises from our system.