Human as Real-Time Sensors of Social and Physical Events: A Case Study of Twitter and Sports Games

TL;DR

This paper demonstrates how Twitter can be used as a real-time sensor to detect social and physical events, achieving high accuracy and low latency, with potential applications in broadcasting and advertising.

Contribution

It introduces an efficient data collection and event recognition method for Twitter, validated through NFL game event detection with high accuracy and timeliness.

Findings

Recognized NFL game events within 40 seconds

Achieved up to 90% accuracy in event detection

Proved feasibility of using Twitter for real-time event sensing

Abstract

In this work, we study how Twitter can be used as a sensor to detect frequent and diverse social and physical events in real-time. We devise efficient data collection and event recognition solutions that work despite various limits on free access to Twitter data. We describe a web service implementation of our solution and report our experience with the 2010-2011 US National Football League (NFL) games. The service was able to recognize NFL game events within 40 seconds and with accuracy up to 90%. This capability will be very useful for not only real-time electronic program guide for live broadcast programs but also refined auction of advertisement slots. More importantly, it demonstrates for the first time the feasibility of using Twitter for real-time social and physical event detection for ubiquitous computing.