Automated Rumor Detection and Visualization

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This document summarizes automated rumor detection and visualization tools developed through EU research projects PHEME and InVID. It describes UNEP Live Web Intelligence for monitoring progress on UN Sustainable Development Goals, the US Election 2016 Web Monitor for analyzing alternative facts during the US election, and techniques like topic classification, stance classification, and cluster analysis used in both projects to verify Twitter and video content. Contact information and links are provided for each tool.

Presentations & Public Speaking

How to Analyze in an Alternative Facts World
Automated Rumor Detection and
Visualization
UNEP Live Web Intelligence | US Election 2016 Web Monitor
Results of the EU Research Projects PHEME and InVID
www.weblyzard.com/showcases
www.weblyzard.com/research
Speaker: Company:
Arno Scharl MODUL University Vienna, webLyzard technology @webLyzard
@_FIBEP
#FIBEP
#WMIC17
Twitter:

SUSTAINABLE DEVELOPMENT GOALS
UNEP Live Web Intelligence
www.weblyzard.com/unep-live
POLITICAL COMMUNICATION
US Election 2016 Web Monitor
www.weblyzard.com/us-election-2016
PHEME – VERACITY INTELLIGENCE
Verification of Twitter Content Streams
www.weblyzard.com/pheme
INVID – IN VIDEO VERITAS
Verification of User-Generated Videos
www.weblyzard.com/invid

UNEP Live Web
Intelligence
www.weblyzard.com/unep-live
Developed by the Department of New Media Technology of
MODUL University Vienna and powered by webLyzard technology
unep.ecoresearch.net ▪ uneplive.unep.org

„ … has led to wild claims on both sides of the divide.“

US Election 2016
Web Monitor
us2016.weblyzard.com
Developed at the Department of New Media Technology of
MODUL University Vienna; powered by webLyzard technology
www.weblyzard.com/us-election-2016-web-monitor

Topic Classification
Cluster Analysis
www.pheme.euPHEMEFP7

Stance Classification
Cluster Analysis
www.pheme.euPHEMEFP7

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Automated Rumor Detection and Visualization

1. How to Analyze in an Alternative Facts World Automated Rumor Detection and Visualization UNEP Live Web Intelligence | US Election 2016 Web Monitor Results of the EU Research Projects PHEME and InVID www.weblyzard.com/showcases www.weblyzard.com/research Speaker: Company: Arno Scharl MODUL University Vienna, webLyzard technology @webLyzard @_FIBEP #FIBEP #WMIC17 Twitter:

2. SUSTAINABLE DEVELOPMENT GOALS UNEP Live Web Intelligence www.weblyzard.com/unep-live POLITICAL COMMUNICATION US Election 2016 Web Monitor www.weblyzard.com/us-election-2016 PHEME – VERACITY INTELLIGENCE Verification of Twitter Content Streams www.weblyzard.com/pheme INVID – IN VIDEO VERITAS Verification of User-Generated Videos www.weblyzard.com/invid

3. UNEP Live Web Intelligence www.weblyzard.com/unep-live Developed by the Department of New Media Technology of MODUL University Vienna and powered by webLyzard technology unep.ecoresearch.net ▪ uneplive.unep.org

4. „ … has led to wild claims on both sides of the divide.“

8. US Election 2016 Web Monitor us2016.weblyzard.com Developed at the Department of New Media Technology of MODUL University Vienna; powered by webLyzard technology www.weblyzard.com/us-election-2016-web-monitor

10.

11.

12. News Media

13. Twitter

14. Twitter

15. Twitter

16. Topic Classification Cluster Analysis www.pheme.euPHEMEFP7

17. Stance Classification Cluster Analysis www.pheme.euPHEMEFP7

18. www.invid-project.euInVIDH2020

19. www.invid-project.euInVIDH2020

20. Chrome Extension goo.gl/Fo8i73

21. SUSTAINABLE DEVELOPMENT GOALS UNEP Live Web Intelligence www.weblyzard.com/unep-live POLITICAL COMMUNICATION US Election 2016 Web Monitor www.weblyzard.com/us-election-2016 PHEME – VERACITY INTELLIGENCE Verification of Twitter Content Streams www.weblyzard.com/pheme INVID – IN VIDEO VERITAS Verification of User-Generated Videos www.weblyzard.com/invid

Automated Rumor Detection and Visualization

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