Detecting Events From Twitter In Real-Time

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dc.contributor.advisorZhong, Linen_US
dc.contributor.committeeMemberSabharwal, Ashutoshen_US
dc.contributor.committeeMemberSubramanian, Devikaen_US
dc.contributor.committeeMemberVasuderan, Venuen_US
dc.creatorZhao, Siqien_US
dc.date.accessioned2013-09-16T19:15:19Zen_US
dc.date.accessioned2013-09-16T19:15:21Zen_US
dc.date.available2013-09-16T19:15:19Zen_US
dc.date.available2013-09-16T19:15:21Zen_US
dc.date.created2013-05en_US
dc.date.issued2013-09-16en_US
dc.date.submittedMay 2013en_US
dc.date.updated2013-09-16T19:15:21Zen_US
dc.description.abstractTwitter 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationZhao, Siqi. "Detecting Events From Twitter In Real-Time." (2013) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/72070">https://hdl.handle.net/1911/72070</a>.en_US
dc.identifier.slug123456789/ETD-2013-05-358en_US
dc.identifier.urihttps://hdl.handle.net/1911/72070en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectSocial networksen_US
dc.subjectTwitteren_US
dc.subjectComputer engineeringen_US
dc.titleDetecting Events From Twitter In Real-Timeen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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