publication . Conference object . 2017

video retrieval for multimedia verification of breaking news on social networks

Nixon, Lyndon; Zhu, Shu; Fischer, Fabian; Rafelsberger, Walter; Gobel, Max; Scharl, Arno;
Open Access
  • Published: 27 Oct 2017
  • Publisher: ACM Press
Abstract
This paper presents an approach to automatically detecting breaking news events from social media streams, using event detection to collect in near real time relevant video documents from social networks regarding that breaking news. A visual analytics dashboard provides access to the results of the content processing pipeline, providing a rich interactive interface to explore emerging stories and select video material around those stories for verification.
Subjects
free text keywords: Social Network Retrieval, Social Media Retrieval, Social Media Extraction, Breaking News Detection, Story Detection, World Wide Web, Video retrieval, Social network, business.industry, business, Social media, Dashboard (business), Visual analytics, Computer science, Multimedia, computer.software_genre, computer
Funded by
EC| InVID
Project
InVID
In Video Veritas – Verification of Social Media Video Content for the News Industry
  • Funder: European Commission (EC)
  • Project Code: 687786
  • Funding stream: H2020 | IA
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publication . Conference object . 2017

video retrieval for multimedia verification of breaking news on social networks

Nixon, Lyndon; Zhu, Shu; Fischer, Fabian; Rafelsberger, Walter; Gobel, Max; Scharl, Arno;