How significant is algorithmic personalization in searches for political parties and candidates?
Sue Halpern June 8, 2017
Prototype Politics: Technology-Intensive Campaigning and the Data of Democracy by Daniel Kreiss Oxford University Press, 291 pp., $99.00; $27.95 (paper)
Hacking the Electorate: How Campaigns Perceive Voters by Eitan D. Hersch Cambridge University Press, 261 pp., $80.00; $30.99 (paper)
Donald Trump; drawing by James Ferguson
Not long after Donald Trump’s surprising presidential victory, an article published in the Swiss weekly Das Magazin, and reprinted online in English by Vice, began churning through the Internet. While pundits were dissecting the collapse of Hillary Clinton’s campaign, the journalists for Das Magazin, Hannes Grassegger and Mikael Krogerus, pointed to an entirely different explanation—the work of Cambridge Analytica, a data science firm created by a British company with deep ties to the British and American defense industries.According to Grassegger and Krogerus, Cambridge Analytica had used psychological data culled from Facebook, paired with vast amounts of consumer information purchased from data-mining companies, to develop algorithms that were supposedly able to identify the psychological makeup of every voter in the American electorate. The company then developed political messages tailored to appeal to the emotions of each one. As the New York Times reporters Nicholas Confessore and Danny Hakim described it: A voter deemed neurotic might be shown a gun-rights commercial featuring burglars breaking into a home, rather than a defense of the Second Amendment; political ads warning of the dangers posed by the Islamic State could be targeted directly at voters prone to anxiety….Even more troubling was the underhanded way in which Cambridge Analytica appeared to have obtained its information. Using an Amazon site called Mechanical Turk, the company paid one hundred thousand people in the United States a dollar or two to fill out an online survey. But in order to receive payment, those people were also required to download an app that gave Cambridge Analytica access to the profiles of their unwitting Facebook friends.
By Elizabeth Denham, Information Commissioner.
In March we announced we were conducting an assessment of the data protection risks arising from the use of data analytics, including for political purposes.
Engagement with the electorate is vital to the democratic process. Given the big data revolution it is understandable that political campaigns are exploring the potential of advanced data analysis tools to help win votes. The public have the right to expect that this takes place in accordance with the law as it relates to data protection and electronic marketing.
“The tech industry is in the middle of a massive, uncontrolled social experiment. Having made commercial mass surveillance the economic foundation of our industry, we are now learning how indiscriminate collections of personal data, and the machine learning algorithms they fuel, can be put to effective political use. Unfortunately, these experiments are being run in production. Our centralized technologies could help authoritarians more than they help democracy, and the very power of the tools we’ve built for persuasion makes it difficult for us to undo the damage done. What can concerned people in the tech industry do to seize a dwindling window of opportunity, and create a less monstrous online world?”
The recent election, which took place beneath a cloud of fake news, revealed that Americans cloister in like-minded online communities. Since then, it’s become increasingly fashionable to complain about the polarizing power of the Internet. Everyone from Katy Perry to Barack Obama to the Pope has lamented the social-media echo chamber and its corrosive effects on society.
If the Internet is truly tearing the nation apart, though, it’s hard to see that in the data. Plugged-in millennials aren’t the ones who seem to be getting more polarized, according to a new Stanford study. In fact, it’s the opposite: Over the past 20 years, political acrimony spiked among older Americans — the same people who are least likely to use the Internet.
Daags na Trumps overwinning bij de Amerikaanse verkiezingen, wezen journalisten en masse één boosdoener aan: Facebook. De social media-site was de voornaamste nieuwsbron voor veel Amerikanen, maar het systeem erachter zou mensen eenzijdig nieuws hebben voorgeschoteld.Nu is er een tool waarmee we kunnen checken of dat in Nederland ook gebeurt: fb.tr.ex.
It has been argued that the Internet and social media increase the number of available viewpoints, perspectives, ideas and opinions available, leading to a very diverse pool of information. However, critics have argued that algorithms used by search engines, social networking platforms and other large online intermediaries actually decrease information diversity by forming so-called “filter bubbles”. This may form a serious threat to our democracies. In response to this threat others have developed algorithms and digital tools to combat filter bubbles. This paper first provides examples of different software designs that try to break filter bubbles. Secondly, we show how norms required by two democracy models dominate the tools that are developed to fight the filter bubbles, while norms of other models are completely missing in the tools. The paper in conclusion argues that democracy itself is a contested concept and points to a variety of norms. Designers of diversity enhancing tools must thus be exposed to diverse conceptions of democracy.
Trump’s presidential election victory is the most successful digital voter suppression operation in American history. The secret weapons in Trump’s digital arsenal were Project Alamo, his database of 220 million people in the United States, and the Facebook Advertising Platform. By leveraging Facebook’s sophisticated advertising tools, including Facebook Dark Posts, Facebook Audience-Targeting, and Facebook Custom Audiences from Customer Lists, the Trump campaign was able to secretly target Hillary Clinton’
The debate over who, in the media and in the IT scene, is responsible for Trump’s victory is just starting. I have been claiming for a long time that the issue is not an algorithmic one. The “algorithmic” candidate was Hillary Clinton: she embraced the big data targeting approach that helped Obama’s victory in 2012, and it seems that her campaign was coordinated by a data processing system called Ada. On the contrary, the secret of the Talking Combover’s victorious campaign is the exploitation of crowds of “click workers”, most of them located on the other side of the globe. If Hillary Clinton spent $ 450 millions, by comparison Trump spent less (about half of her budget), by under-paying subcontractors recruited on micro-work platforms. An army of digital pieceworkers living in developing countries Maybe you have read the bitter-sweet news about a Singapore teenager who helped create a Prezi presentation for Trump. She was recruited on Fiverr, a platform where, for a few bucks, you
n November 7, 2016, the day before the US election, I compared the number of social media followers, website performance, and Google search statistics of Hillary Clinton and Donald Trump. I was shocked when the data revealed the extent of Trump’s popularity. He had more followers across all social platforms and his posts had much higher engagement rates. I noticed that the second most popular article shared on social media in the last six months with words “Donald Trump” in the headline, “Why I’m Voting