Twitter is one of the most popular online social networking sites. It provides a unique and novel venue of publishing: it has over 500 million active users around the globe; tweets are brief, limited to 140 characters, an ideal way for people to publish spontaneously. As a result, Twitter has the short delays in reflecting what its users perceive, compared to other venues such as blogs and product reviews.
We design and implement SportSense, which exploits Twitter users as human sensors of the physical world to detect major events in real-time. Using the National Football League (NFL) games as a targeted domain, we report in-depth studies of the delay and trend of tweets, and their dependence on other properties. We present event detection method based on these findings, and demonstrate that it can effectively and accurately extract major game events using open access Twitter data. SportSense has been evolving during the 2010-11 and 2011-12 NFL seasons and it has been collecting hundreds of millions tweets. We provide SportSense API for developers to use our system to create Twitter-enabled applications.
| Identifer | oai:union.ndltd.org:RICE/oai:scholarship.rice.edu:1911/72070 |
| Date | 16 September 2013 |
| Creators | Zhao, Siqi |
| Contributors | Zhong, Lin |
| Source Sets | Rice University |
| Language | English |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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