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Context Aggregation and Analysis: A tool for User-Generated Video Verification

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The tool aims to facilitate the verification of user-generated videos posted by three well-known platforms – YouTube, Facebook and Twitter. It collects information surrounding the video, analyses and filters it and creates a verification report that is then presented to the end-user (journalist) who is responsible to inspect the verification cues and decide about the video veracity.

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Context Aggregation and Analysis: A tool for User-Generated Video Verification

  1. 1. Context Aggregation and Analysis: A Tool for User- Generated Video Verification Olga Papadopoulou, Dimitrios Giomelakis, Lazaros Apostolidis, Symeon Papadopoulos, Yiannis Kompatsiaris Journalism department of AUTH 12 December 2019
  2. 2. CERTH was established in 2000 • 5 institutes, >700 employees (ITI is the largest with >300 employees) • 1200 projects, 1100 international collaborations • Among top-10 EU institutions in attracting competitive research projects MKLab is among the biggest ITI labs with >60 researchers (20+ post-docs) • Key areas: multimedia, social media, computer vision, data mining, machine learning • Since 2003, involved in more than 60 research projects and published >600 research papers MeVer is a team that develops technologies and services for the detection of media- based disinformation - https://mever.iti.gr/web/ • Datasets - https://mever.iti.gr/web/resources/ • Services - https://mever.iti.gr/web/resources/ • Context Aggregation and Analysis • Near duplicate detection • Image forensics Follow us https://twitter.com/meverteam MeVer @ MKLab - CERTH-ITI
  3. 3. InVID – WeVerify Plugin https://weverify.eu/verification-plugin/ >17.000 users all over the world CAA is integrated as component of the Verification plugin (Analysis)
  4. 4. User generated videos Staged Reuse Tampered Croatia right now - Fifa World Cup Final 2018 $250,000 car gets windshield SMASHED by kid on a skateboard!!! https://www.youtube.com/watch?v=VBa4D9D6Gng Lion Takes Revenge On Trophy Hunter! https://www.youtube.com/watch?v=l7yt-VPYtOA https://www.youtube.com/watch?v=l7yt-VPYtOA
  5. 5. Context Aggregation and Analysis Platform APIs CAA COMPONENTS Verification report https://caa.iti.gr A tool that aims to facilitate the verification of user-generated videos. Provide URL Start Verification
  6. 6. Video and account metadata Metadata about the video and the source that posted the video: • Video title • Video description • Create time • ….. • Mentioned locations – extracted by the text (title, description) • Channel name • Channel creation time
  7. 7. Video Comments 1. All comments left below the video 2. Verification comments – filtered by a list of predefined verification related keywords helpful for verification 3. Link comments, comments that contain links to external sources 4. Free text comments, the user can provide his/her own keyword and create subset
  8. 8. Reverse image search The video thumbnails as returned by the Platform APIs Buttons for applying reverse image search are included below each thumbnail for: 1. Google reverse image search 2. Yandex reverse image search
  9. 9. Twitter timeline • Tweets sharing the URL of the video in question are collected and visualized in a timeline. • The red line indicates the time that the video was posted. • Clicking on each box (tweet) the text of the tweet appears along with a link to the Tweet Verification Assistant ‘check tweet veracity’ which extracts a score indicating the tweet credibility.
  10. 10. Verification AI score A score in the range of [0 1]. The higher the score the less credible the video is. The score is extracted using a machine learning method. Although it is helpful, indicator the accuracy of the algorithm is ~70% so it should be considered for the verification process but the user should not leverage only on it for the final result.
  11. 11. Video comments Video commentsVerification-related Available in 7 languages Links User- defined keywords English Keywords: lies, fake, wrong, lie, confirm, where, location, lying, false, incorrect, misleading, propaganda, liar
  12. 12. Twitter Timeline Twitter timeline:  The tweets sharing the submitted video URL for YouTube and Facebook videos.  The retweets of a submitted Twitter video. A tweet is posted couple of hours after the Video was shared on YouTube (redline) and explains that the claim of ISIS being the target of the bombing is false. Claim: Bombing over ISIS area
  13. 13. User Study Tasks:  Debunking the 200 fake videos of the FVC  Verifying the 180 real videos of the FVC Users:  A male with journalistic background  A female with computer engineering background Procedure: 1. Submit a video URL to the tool 2. Check and analyse the produced verification report 3. Decide about the video veracity 4. Record the results and the time spent on the task Labels:  True: If a fake/real video is debunked/verified  False: if the debunking or veryfying of a fake/real video fails  Uncertain: there are indicators that create doubts about the video credibility but there is no concrete evidence proving that the video is fake or real. Is Debunked # videos Time (sec) True 132 208 False 46 272 Uncertain 22 270 ~70% of the fake videos were succesfully debunked Is Verified # videos True 140 False 29 Uncertain 11 ~80% of the real videos were succesfully verified
  14. 14. Report Results 1. Start Timer – Don’t forget to stop it when the verification process is completed 2. Select the Verification Label 3. How certain are you for the Verification Label 4. Verification Features 5. Description: a free text description of the procedure that you followed to verify the video 6. Submit https://caa.iti.gr/annotation/
  15. 15. Thank you for your attention! https://caa.iti.gr https://twitter.com/meverteam Follow us on Twitter: Media Verification team website https://mever.iti.gr/web/ Contact us: Olga Papadopoulou - olgapapa@iti.gr Symeon Papadopoulos – papadop@iti.gr

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