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Event Analytics on Social Media: Challenges and Solutions

Abstract Social media platforms such as Twitter, Facebook, and blogs have emerged as valuable

- in fact, the de facto - virtual town halls for people to discover, report, share and

communicate with others about various types of events. These events range from

widely-known events such as the U.S Presidential debate to smaller scale, local events

such as a local Halloween block party. During these events, we often witness a large

amount of commentary contributed by crowds on social media. This burst of social

media responses surges with the "second-screen" behavior and greatly enriches the

user experience when interacting with the event and people's awareness of an event.

Monitoring and analyzing this rich and continuous flow of ... (more)
Created Date 2014
Contributor Hu, Yuheng (Author) / Kambhampati, Subbarao (Advisor) / Horvitz, Eric (Committee member) / Krumm, John (Committee member) / Liu, Huan (Committee member) / Sundaram, Hari (Committee member) / Arizona State University (Publisher)
Subject Computer science / data mining / event analysis / event detection / sentiment analysis / social media / twitter
Type Doctoral Dissertation
Extent 213 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Computer Science 2014
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis