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How Fake News Spreads Through Online Social Networks

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Dive into the fascinating world of network science, which represents people and information by the connections and interactions they share. I’ll demonstrate that network science is powerful and network visualization is beautiful, using a series of recent cases to show how information and misinformation (aka “fake news”) spread through online social networks such as Twitter and Facebook. Find out how connecting two dots by a line over and over becomes a striking and effective way to study the world we live in.

Note: This slidedeck is for the presentation by Anatoliy Gruzd at the 2019 CRAM event in Toronto: https://cramtoronto.com/

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How Fake News Spreads Through Online Social Networks

  1. 1. ONE-WAY, TOP-DOWN DISSEMINATION MODEL Photo by Chris Jagers Photo by Pexels from pixabay
  2. 2. NETWORK EFFECT Photo by Thomas Jensen Photo by Gerd Altmann from Pixabay
  3. 3. NETWORK EFFECT #OccupyGezi Supporters in Victoria, BCPhoto credit: Anatoliy Gruzd Photo credit: Karl Schönswetter
  4. 4. EXAMPLE: NETWORK EFFECT IN 2008, THE ‘NETWORK EFFECT’ HELPED (IN PART) TO SEND A LITTLE-KNOWN 1ST TERM U.S. SENATOR TO THE WHITE HOUSE. Image credit: Brendan Loy
  5. 5. Image credits: Lou Gold; Photo-Mix http://obamawhitehouse.gov.archivesocial.com
  6. 6. VIRTUAL NO MORE THE USE OF SOCIAL MEDIA DURING POPULAR POLITICAL UPRISINGS
  7. 7. 2016 U.S. PRESIDENTIAL ELECTION U.K.’S BREXIT REFERENDUM VIRTUAL NO MORE
  8. 8. VIRTUAL NO MORE Photo licensed under CC BY-SA-NC Photo is licensed under CC BY-SA-NC 2018 FEDERAL ELECTION IN BRAZIL 2019 PRESIDENTIAL ELECTION IN UKRAINE
  9. 9. Misinformation spread like wild fire over social media But this is not a bug. It’s a feature. Image credit: Geralt
  10. 10. Canada is not immune to this
  11. 11. Canada is not immune to this The ‘State of Social Media’ report is avail. at socialmedialab.ca
  12. 12. Research Questions WHAT HOW
  13. 13. Common types of misinformation Misleading content Fabricated content False connection False context Manipulated content (Derakhshan & Wardle, 2017)
  14. 14. This fabricated photo first made the rounds after the 2011 Hurricane Irene Misleading content Fabricated content False connection False context Manipulated content http://mentalfloss.com/article/12943/10-fake-photos-hurricane-sandy-went-viral
  15. 15. Misleading content Fabricated content False connection False context Manipulated content
  16. 16. Misleading content Fabricated content False connection False context Manipulated content “For child death reports, 79.4% received >1 vaccine on the same day.” “ …sudden infant death syndrome (n = 544 [44%])” “Because SIDS peaks at a time when children are receiving many recommended vaccinations, it would not be unexpected to observe a coincidental close temporal relationship between vaccination and SIDS”
  17. 17. Research Questions WHAT HOW
  18. 18. USING ‘NETWORK SCIENCE’ TO TRACK & STUDY THE SPREAD OF MISINFORMATION
  19. 19. @John @Marry @AnneNodes = Twitter accounts (person/org) Network Ties = “Who retweeted/ replied/mentioned whom” Tie strength = The number of retweets (or replies or mentions) A COMMMUNICATION NETWORK ON TWITTER
  20. 20. Network Ties DISCOVERING A NETWORK STRUCTURE ONE TWEET AT THE TIME @Phmai @RyersonU @Gruzd
  21. 21. WHO TWEETS ABOUT #CramTO @CramToronto @OCAD @yorkuniversity @RyersonU @UofT @CBCToronto
  22. 22. EXAMPLES OF DIFFERENT INFORMATION PROPAGATION MODELS ON TWITTER
  23. 23. Example 1 Sharing a news story about the 2014 Euromaidan revolution in Ukraine News source Star-shaped Network Configuration
  24. 24. Example 2 Information sharing and conversations about a Netflix show called “13 Reasons Why” Show’s main account (info source) Information propagation & discussions Star-shaped Configuration with a Long Tail
  25. 25. @gruzd Twitter chatter about different sporting events during the 2012 Olympics in London Example 3 Photo by Charles 🇵🇭 on Unsplash Multiple Clusters
  26. 26. HOW DO THESE NETWORK VISUALIZATIONS HELP US STUDY MISINFORMATION?
  27. 27. EXAMPLE OF ELECTION INTERFERENCE CAMPAIGN ON TWITTER: RUSSIAN INTERNET RESEARCH AGENCY / IRA ACCOUNTS 2011 - 2018 3,836 IRA-associated accounts 9M tweets & RTs https://about.twitter.com/en_us/values/elections-integrity.html#data 200k tweets & RTs
  28. 28. Red nodes = known IRA accounts Activities of IRA Twitter accounts 1 month before the 2016 U.S. Presidential Election 38,000 accounts 1% (381) IRA accounts >200,000 tweets & RTs
  29. 29. Activities of IRA Twitter accounts 1 month before the 2016 U.S. Presidential Election 38,000 accounts 1% (381) IRA accounts >200,000 tweets & RTs Example: Source:https://www.reddit.com/r/The_Donald Red nodes = known IRA accounts
  30. 30. Activities of IRA Twitter accounts 1 month before the 2016 U.S. Presidential Election 38,000 accounts 1% (381) IRA accounts >200,000 tweets & RTs Red nodes = known IRA accounts
  31. 31. Red nodes = known IRA accounts Activities of IRA Twitter accounts 1 month before the 2018 U.S. Presidential Election pro-Trump and anti-Hillary cluster
  32. 32. Red nodes = known IRA accounts Activities of IRA Twitter accounts 1 month before the 2018 U.S. Presidential Election #BlackLivesMatter cluster
  33. 33. Red nodes = known IRA accounts Activities of IRA Twitter accounts 1 month before the 2018 U.S. Presidential Election pro-Putin cluster
  34. 34. Red nodes = known IRA accounts Activities of IRA Twitter accounts 1 month before the 2018 U.S. Presidential Election Sports & Entertainment cluster
  35. 35. Red nodes = known IRA accounts Activities of IRA Twitter accounts 1 month before the 2018 U.S. Presidential Election
  36. 36. RECAP This is how by CONNECTING TWO DOTS BY A LINE over & over again, and with the help of NETWORK SCIENCE, we study online misinformation campaigns to DETECT & COUNTER FUTURE ONES. 1 65 3 2 4

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