consequential data

This post ushers in a theme of reflection. Throughout the coming months, I will use this space as a sounding board for considerations that arise from our readings. This first post is a brief investigation into the 2016 US Presidential Election and how user data was harnessed to create curated, self-reflexive chambers that ultimately brought the legitimacy of the electoral process into question.

The contemporary online individual finds themselves trapped within cyclical discourses and echo chambers which make bridging the gap between ideas more complicated. When considering a controversial topic, as seems to be the norm these days, individuals often allow bias and personal viewpoints to impact their idea of credibility or leniency with the data they are given. There has been significant work put into the creation of frameworks to understand how individuals can ultimately escape the echo chambers they find themselves in and ultimately encounter alternative viewpoints. One such framework, titled Bias-Trust is designed to minimize those previously mentioned signals that cause confirmation bias. This study aligns with Allcott and Gentzkow (2017) in recognizing social media as a meaningful source of political information. While the notion that fake news leads to a less informed citizenry seems obvious, it’s importance is often understated. A knowledgeable public is critical to a well-functioning democracy. There were very real concerns that the 2016 US presidential election was significantly swayed by fake news. An example of this phenomenon was an article that rose to find itself being the “most clicked” story about three months ahead of the election. The article was titled “Pope Francis Shocks World, Endorses Donald Trump for President, Releases Statement”. The story was entirely fictitious. However, it amassed over 900,000 shares on Facebook (Bakir and McStay 2017). In a proximal study, the conclusion was made that for the outcome of the election to have been swayed, a fake news article would have had to hold the same level of persuasiveness as about 36 traditional tv ad (ibid). The amount of fear concerning this possibility in the immediate aftermath of the election was caused Mark Zuckerberg, the CEO of Facebook, to release a statement declaring that fake news on the platform did not influence the election. Regardless of the platform’s stance on the matter, the reality of these fake news stories being engaged with on such a large scale is noteworthy.  Some of the fake news stories that are spread can be easily deciphered by the public as misleading or fictitious (ibid), there are others that do a better job of masking themselves as legitimate news sources or articles.

Allcott, H. and Gentzkow, M. (2017) covers the 2016 US Presidential Election specifically while also discussing the challenge that echo chambers and filter bubbles place on individuals and their capacity to engage critically with the content they view. They found that about 14% of American adults value social media as their most important source of election news. When investigating the relationship between fake news and ideological polarization, it is helpful to explore more about the psychological background of ideological polarization in the past two decades. Sophr (2017) provides an empirical currency to this discourse as the political history of polarization and its increased prominence in the recent election are a focus for many a case study. It evaluates the debate over whether polarization has increased due to our new systems of media consumption. The author examines the roles that specific social media companies play in the shaping of these ideological landscapes. The convergence of these companies as both technology firms and media companies is something that their article highlights. Sophr concludes that this convergence is at the heart of the shift from traditional news agencies and media to faster and more easily digestible news built on the back of Big Data and content curation.

Allcott, H. and Gentzkow, M. 2017. Social Media and Fake News in the 2016 Election. Journal of Economic Perspectives, 31(2), pp.211-236.

Bakir, V. and McStay, A., 2017. Fake News and The Economy of Emotions. Digital Journalism, 6(2), pp.154-175.

Spohr, D. 2017. Fake news and ideological polarization. Business Information Review, 34(3), pp.150-160.

3 thoughts on “consequential data

  1. A solid and excellently sourced overview into some of the downsides of how voters engage with politics in the modern information era. As we all move further and further away from traditional news and into the wild west of social media, it seems we are opening a pandora’s box of fake news and self-reinforcing, self-referential echo chambers. Interestingly, this is not actually the first big change in how we consume news, but possibly an addendum to a previous one. The move from newspapers to news television, and particularly the 24-hour news cycle was the start. Worse, social media is now warping what came before as more traditional media try to compete for views.

    Liked by 1 person

  2. Super interesting and informative post Jack! It’s strange how Trump’s use of Twitter seems almost normal by now, yet it’s rare for the global public to have such insight into a world leader’s thoughts and feelings (if they are genuine, I guess.) And with another election so close it’d be interesting to compare how people’s attitudes towards social media spreading news has changed. Facebook is at least acknowledging the way it’s platform can be used to spread information, and Twitter now posts warnings on certain tweets. I wonder how much it’s helped.

    Like

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