Veracity and velocity of social media content during breaking news: analysis of November 2015 Paris shootings
Wiegand, Stefanie and Middleton, Stuart (2016) Veracity and velocity of social media content during breaking news: analysis of November 2015 Paris shootings At SNOW Workshop at WWW 2016 Conference, Canada. 12 Apr 2016. (doi:10.1145/12345.67890 10.1145/2872518.2890095).
Social media sources are becoming increasingly important in journalism. Under breaking news deadlines semi-automated support for identification and verification of content is critical. We describe a large scale content-level analysis of over 6 million Twitter, You Tube and Instagram records covering the first 6 hours of the November 2015 Paris shootings. We ground our analysis by tracing how 5 ground truth images used in actual news reports went viral. We look at velocity of newsworthy content and its veracity with regards trusted source attribution. We also examine temporal segmentation combined with statistical frequency counters to identify likely eyewitness content for input to real-time breaking content feeds. Our results suggest attribution to trusted sources might be a good indicator of content veracity, and that temporal segmentation coupled with frequency statistical metrics could be used to highlight in real-time eyewitness content if applied with some additional text filters.
|Item Type:||Conference or Workshop Item (Paper)|
|Digital Object Identifier (DOI):||doi:10.1145/12345.67890 10.1145/2872518.2890095|
|Venue - Dates:||SNOW Workshop at WWW 2016 Conference, Canada, 2016-04-12 - 2016-04-12
|Date Deposited:||19 Apr 2016 11:07|
|Last Modified:||22 Feb 2017 06:03|
REVEALing hidden concepts in Social Media (REVEAL)
Funded by: European Commission - FP7 (610928)
1 November 2013 to 31 October 2016
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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