Framework for Real-Time Event Detection using Multiple Social Media Sources Katragadda, Satya Benton, Ryan Raghavan, Vijay 2016-12-29T00:42:57Z 2016-12-29T00:42:57Z 2017-01-04
dc.description.abstract Information about events happening in the real world are generated online on social media in real-time. There is substantial research done to detect these events using information posted on websites like Twitter, Tumblr, and Instagram. The information posted depends on the type of platform the website relies upon, such as short messages, pictures, and long form articles. In this paper, we extend an existing real-time event detection at onset approach to include multiple websites. We present three different approaches to merging information from two different social media sources. We also analyze the strengths and weaknesses of these approaches. We validate the detected events using newswire data that is collected during the same time period. Our results show that including multiple sources increases the number of detected events and also increase the quality of detected events. \
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2017.208
dc.identifier.isbn 978-0-9981331-0-2
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Event Detection
dc.subject Social media
dc.subject Heterogeneous Data Sources
dc.title Framework for Real-Time Event Detection using Multiple Social Media Sources
dc.type Conference Paper
dc.type.dcmi Text
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