2012/05/14 by Siqi Zhao, Zhao, Siqi, Lin Zhong +9
Computer Science · Economics, Econometrics and Finance · Social Sciences · #Digital Games and Media #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Sports Analytics and Performance #Video Analysis and Summarization
paper · pdf · doi:10.48550/arxiv.1205.3212
openalex publication_date 2012/05/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We report our experience in building a working system, SportSense (http://www.sportsense.us), which exploits Twitter users as human sensors of the physical world to detect events in real-time. Using the US National Football League (NFL) games as a case study, we report in-depth measurement studies of the delay and post rate of tweets, and their dependence on other properties. We subsequently develop a novel event detection method based on these findings, and demonstrate that it can effectively and accurately extract game events using open access Twitter data. SportSense has been evolving during the 2010-11 and 2011-12 NFL seasons and is able to recognize NFL game big plays in 30 to 90 seconds with 98% true positive, and 9% false positive rates. Using a smart electronic TV program guide, we show that SportSense can utilize human sensors to empower novel services.