Google and Facebook Anti–Fake News Efforts
The social media platforms and search engines them- selves have made some efforts to help detect and flag fake news. Facebook created an “immune system” to
Combating Fake News in the Digital Age Joanna M. Burkhardt
help protect itself from infection by bots.40 Google announced that it will increase its regulation of adver- tising and linked-to websites.41 Facebook has turned over the verification of information to five lead- ing fact-checking organizations.42 Facebook has also initiated a feature in parts of Europe called Related Articles, which provides readers with access to the results of fact-checking of original stories.43 Google Digital News Initiative is creating programs to help users verify information themselves with Factmata. Overall, these attempts are reactive at best. The sheer volume of potential misinformation and the difficulty in identifying and shutting down bot accounts make these attempts seem feeble.
Factmata http://factmata.com/
It seems that the battle of the computer program- mers will continue indefinitely. When one side devel- ops a new means of manipulating information to mis- lead, misinform, or unduly influence people, the other side finds a way to counter or at least slow the ability to make use of the new idea. This cycle continues in a seemingly endless loop. Using technology to iden- tify and stop fake news is a defensive game. There does not appear to be a proactive means of eliminat- ing fake news at this time. Money, power, and politi- cal influence motivate different groups to create com- puter-driven means of human control.
Notes 1. Andrew Zaleski, “How Bots, Twitter, and Hackers
Pushed Trump to the Finish Line,” Backchannel, Wired, November 10, 2016, https://www.wired .com/2016/11/how-bots-twitter-and-hackers -pushed-trump-to-the-finish-line/; Alessandro Bessi and Emilio Ferrara, “Social Bots Distort the 2016 U.S. Presidential Election Online Discussion,” First Monday 21, no. 11 (November 7, 2016), http:// journals.uic.edu/ojs/index.php/fm/rt/printer Friendly/7090/5653.
2. Tony Haile, “What You Think You Know about the Web Is Wrong,” Time.com, March 9, 2014, http:// time.com/12933/what-you-think-you-know -about-the-web-is-wrong/.
3. Don Evon, “Nope Francis,” Snopes, July 24, 2016, www.snopes.com/pope-francis-donald-trump -endorsement/.
4. Marc Fisher, John Woodrow Cox, and Peter Her- mann, “Pizzagate: From Rumor, to Hashtag, to Gun- fire in D.C.,” Washington Post, December 6, 2016, https://www.washingtonpost.com/local/pizza gate-from-rumor-to-hashtag-to-gunfire-in-dc /2016/12/06/4c7def50-bbd4-11e6-94ac-3d32 4840106c_story.html.
5. D. Parvaz, “The Arab Spring, Chronicled Tweet by Tweet,” Al Jazeera English, November 6, 2011, www .aljazeera.com/indepth/features/2011/11/2011 113123416203161.html; Sara El-Khalili, “Social Media as a Government Propaganda Tool in Post- revolutionary Egypt,” First Monday 18, no. 3 (March 4, 2013), http://firstmonday.org/ojs/index.php/fm /rt/printerFriendly/4620/3423.
6. “Twitter Served as a Lifeline of Information During Hurricane Sandy,” Pew Research Center, FactTank, October 28, 2013, www.pewresearch.org/fact-tank /2013/10/28/twitter-served-as-a-lifeline-of-infor mation-during-hurricane-sandy/.
7. David Turner, Michael Schroeck, and Rebecca Shock- ley, Analytics: The Real-World Use of Big Data in Fi- nancial Services, executive report (Somers, NY: IBM Global Services, 2013).
8. Kate Crawford, “The Hidden Biases in Big Data,” Harvard Business Review, April 1, 2013, https://hbr .org/2013/04/the-hidden-biases-in-big-data.
9. Dirk Helbing, Bruno S. Frey, Gerd Gigerenzer, Ernst Hafen, Michael Hagner, Yvonne Hofstetter, Jeroen van den Hoven, Roberto V. Zicari, and Andrej Zwit- ter, “Will Democracy Survive Big Data and Artificial Intelligence?” Scientific American, February 25, 2017, https://www.scientificamerican.com/article/will -democracy-survive-big-data-and-artificial-intelli gence/; previously published in Scientific American’s sister publication Spektrum der Wissenschaft as “Digi- tale Demokratie statt Datendiktatur.”
10. Steven J. Frenda, Rebecca M. Nichols, and Elizabeth F. Loftus, “Current Issues and Advances in Misinfor- mation Research,” Current Directions in Psychological Science 20, no. 1 (2011): 20–23.
11. Haile, “What You Think You Know.” 12. Igal Zelfman, “Bot Traffic Report 2016,” Imperva
Incapsula Blog, January 24, 2017, https://www.incap sula.com/blog/bot-traffic-report-2016.html.
13. Onur Varol, Emilio Ferrara, Clayton A. Davis, Filippo Menczer, and Alessandro Falmmini, “Online Human- Bot Interactions: Detection, Estimation and Charac- terization,” in Proceedings of the Eleventh Internation- al AAAI Conference on Web and Social Media (ICWSM 2017) (Palo Alto, CA: AAAI Press, 2017), 280.
14. Emilio Ferrara, Onur Varol, Clayton Davis, Filippo Menczer, and Alessandro Flammini, “The Rise of So- cial Bots,” Communications of the ACM 59, no. 7 (July 2016): 96.
15. Philip N. Howard, Pax Technica: How the Internet of Things May Set Us Free or Lock Us Up (New Haven, CT: Yale, 2015), 211.
16. Twitter, Inc., Form 10-Q, Report for the Quarterly Period Ended June 30, 2014, US Securities and Ex- change Commission file number 001-36164, www .sec.gov/Archives/edgar/data/1418091/000156459 014003474/twtr-10q_20140630.htm; Varol et al., “Online Human-Bot Interactions.
17. Charles F. Bond and Bella M. DePaulo, “Accuracy of Deception Judgments,” Personality and Social Psy- chology Review 10, no. 3 (2006): 214–34.
18. Niall J. Conroy, Victoria L. Rubin, and Yimin Chen, “Automatic Deception Detection: Methods for Finding Fake News,” Proceedings of the Association for Information Science and Technology 52, no. 1