Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41362

Framework for Real-Time Event Detection using Multiple Social Media Sources

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Item Summary

Title: Framework for Real-Time Event Detection using Multiple Social Media Sources
Authors: Katragadda, Satya
Benton, Ryan
Raghavan, Vijay
Keywords: Event Detection
Social media
Heterogeneous Data Sources
Issue Date: 04 Jan 2017
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. \
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41362
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.208
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Citizen Journalism and Social Media Minitrack



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