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Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, Social Bots and the post-truth era" - Juan Carlos Medina

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Dataconomy Media
Dataconomy Media

Trump, Brexit, Cambridge Analytica... In the last few years, we have had to confront the consequences of the use and misuse of data science algorithms in manipulating public opinion through social media. The use of private data to microtarget individuals is a daily practice (and a trillion-dollar industry), which has serious side-effects when the selling product is your political ideology. How can we cope with this new scenario?

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Political Data Science: A tale of Fake News, Social Bots and the post-truth era Juan Carlos Medina Serrano
Political Data Science
Social Bots
• Automated social media accounts that try to look like real users by copying their behavior • They decide automatically which users they follow and which tweets they retweet. • Generate texts, some could be original • Purpose: Manipulate public opinion • Part of computational propaganda: Data driven influence ops
• Automated social media accounts that try to look like real users by copying their behavior • They decide automatically which users they follow and which tweets they retweet. • Generate texts, some could be original • Purpose: Manipulate public opinion • Part of computational propaganda Data driven influence ops
What are their effects? • Massive spread of news • Amplification and manipulation of topics • Spread false information: Fake news and conspiracy theories • Shape the environment we are engaging with
How to recognize them? (TWITTER) • Only retweets https://twitter.com/e_pitzky • No retweets, but copied headlines https://twitter.com/wurmreiter • Tweets per day https://twitter.com/VonSchwer (~ 185) How to recognize them? (TWITTER – Data Science) • Anomaly Detection! 1 ) Machine Learning Methods (Classification) 2 ) Heuristic Methods • Botometer: Features: Network, user, temporal, text features
How to recognize them? (TWITTER) • Only retweets https://twitter.com/e_pitzky • No retweets, but copied headlines https://twitter.com/wurmreiter • Tweets per day https://twitter.com/VonSchwer (~ 185) How to recognize them? (TWITTER – Data Science) • Anomaly Detection! 1 ) Machine Learning Methods (Classification) 2 ) Heuristic Methods • Botometer: Features: Network, user, temporal, text features
What about Facebook?
A threat to our democracy?
Bots in the 2016 U.S. Election #pizzagate: A conspiracy spread by bots
Bots in the 2017 German Election #Wahlbetrug: A case of a bot attack
Russian Interference?
Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, Social Bots and the post-truth era" - Juan Carlos Medina
Costs? $95,000
Costs? $95,000
Russian Bots? • 2752 accounts closed by Twitter that “were related” to Russia’s IRA (Internet Research Agency). List compiled and released by the U.S. congress • Badaxy, Ferrara and Lerman (2017) showed that conservatives retweeted Russian trolls 31 more often than liberals.
Russian Bots? • 23,595 tweets from 458 accounts in our German data • 98 accounts were tweeting in German
Russian Bots? Russian Bots in the German media
Die AfD: Social Media King
One year (2017-2018)
September 2017
Last week
Fakes on Facebook
Fakes on Facebook
Fakes on Facebook
Fakes on Facebook
Fake News
• Propaganda and conspiracy theories • Hate and false information propagates faster on social media • Disinformation campaigns • Types: • Deceptive News • Serious Fabrications • Large-scale Hoaxes • Satire
• How to define the problem? - Content-based approaches - Visual - Text - Headline/Text coordination - Social context approaches • How to find good training datasets? Fake News Detection
• How to define the problem? - Content-based approaches - Visual - Text - Headline/Text coordination - Social context approaches • How to find good training datasets? Fake News Detection • Classification Algorithms • Visual: CNN • Text: RNN • Text: Knowledge Graph • Propagation: Graph Algorithms
Polarization
US
Germany
Germany
www.political-dashboard.com

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Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, Social Bots and the post-truth era" - Juan Carlos Medina

  • 1. Political Data Science: A tale of Fake News, Social Bots and the post-truth era Juan Carlos Medina Serrano
  • 4. • Automated social media accounts that try to look like real users by copying their behavior • They decide automatically which users they follow and which tweets they retweet. • Generate texts, some could be original • Purpose: Manipulate public opinion • Part of computational propaganda: Data driven influence ops
  • 5. • Automated social media accounts that try to look like real users by copying their behavior • They decide automatically which users they follow and which tweets they retweet. • Generate texts, some could be original • Purpose: Manipulate public opinion • Part of computational propaganda Data driven influence ops
  • 6. What are their effects? • Massive spread of news • Amplification and manipulation of topics • Spread false information: Fake news and conspiracy theories • Shape the environment we are engaging with
  • 7. How to recognize them? (TWITTER) • Only retweets https://twitter.com/e_pitzky • No retweets, but copied headlines https://twitter.com/wurmreiter • Tweets per day https://twitter.com/VonSchwer (~ 185) How to recognize them? (TWITTER – Data Science) • Anomaly Detection! 1 ) Machine Learning Methods (Classification) 2 ) Heuristic Methods • Botometer: Features: Network, user, temporal, text features
  • 8. How to recognize them? (TWITTER) • Only retweets https://twitter.com/e_pitzky • No retweets, but copied headlines https://twitter.com/wurmreiter • Tweets per day https://twitter.com/VonSchwer (~ 185) How to recognize them? (TWITTER – Data Science) • Anomaly Detection! 1 ) Machine Learning Methods (Classification) 2 ) Heuristic Methods • Botometer: Features: Network, user, temporal, text features
  • 10. A threat to our democracy?
  • 11. Bots in the 2016 U.S. Election #pizzagate: A conspiracy spread by bots
  • 12. Bots in the 2017 German Election #Wahlbetrug: A case of a bot attack
  • 17. Russian Bots? • 2752 accounts closed by Twitter that “were related” to Russia’s IRA (Internet Research Agency). List compiled and released by the U.S. congress • Badaxy, Ferrara and Lerman (2017) showed that conservatives retweeted Russian trolls 31 more often than liberals.
  • 18. Russian Bots? • 23,595 tweets from 458 accounts in our German data • 98 accounts were tweeting in German
  • 19. Russian Bots? Russian Bots in the German media
  • 20. Die AfD: Social Media King
  • 29. • Propaganda and conspiracy theories • Hate and false information propagates faster on social media • Disinformation campaigns • Types: • Deceptive News • Serious Fabrications • Large-scale Hoaxes • Satire
  • 30. • How to define the problem? - Content-based approaches - Visual - Text - Headline/Text coordination - Social context approaches • How to find good training datasets? Fake News Detection
  • 31. • How to define the problem? - Content-based approaches - Visual - Text - Headline/Text coordination - Social context approaches • How to find good training datasets? Fake News Detection • Classification Algorithms • Visual: CNN • Text: RNN • Text: Knowledge Graph • Propagation: Graph Algorithms
  • 33. US

Editor's Notes

  1. Edgar Welch, An oddly disproportionate share of the tweets about Pizzagate appear to have come from, of all places, the Czech Republic, Cyprus and Vietnam,