In the 2016 United States presidential election, for the first time in history, online social media was seen as a huge influence on the results of said election: as more and more people use social media such as Facebook and Instagram as a big part of their news consumption, these platforms have a big role in the formation of political opinions. Especially on Facebook, the spread of fake news and the way recommendation algorithms can create so-called ‘filter bubbles’ were seen as big contributors to the political climate in the United States. Filter bubbles ensure that people will mostly see content which aligns with their existing political beliefs, which in turn can reinforce them and move people even further to one side of the political spectrum. These phenomena can be considered instrumental in aiding the victory of Donald Trump in the 2016 elections. Logically, this would also mean that filter bubbles on Facebook will also have a big influence on the upcoming 2020 elections, which is what we aim to investigate.
Our perception of the world is one that is more and more being governed by algorithms over the last few years: search results, daily feed, recommendations and the ranking of relevant content are all processes in which automated algorithms decide what we see and where we see it. These algorithms almost always base their outputs on your own pre-existing preferences and behaviour, often combined with data on similar users in order to provide you with content that suits you. However, when talking about political news, this also means that users will only see content that suits their own beliefs, which can increase polarization and be beneficial to more controversial and extreme presidential candidates like Donald Trump. Because of the enormous power filter bubbles hold over the way people form their opinions, we consider it highly important to analyze them in regards to their political influence.
To investigate this phenomenon, we will be using Facebook Tracking Exposed, an online web extension which helps to open up the black box that is the Facebook algorithms. Through the browser extension, the tool gathers stories visible in your newsfeed and analyses them for traces of algorithmic manipulation. Though additional personal information is also collected by the tool, such as your Facebook user ID and IP address, the tool ensures the anonymization of data.
In order to achieve this, we will make use of the Facebook Tracking Exposed tool to examine the filter bubbles of multiple profiles that follow different pages and news outlets on Facebook. This will allow us to identify differences in the way news about the upcoming 2020 elections is portrayed. The way Facebook handles its newsfeed can create a filter bubble. The Facebook Tracking Exposed tool will allow us to see how various filter bubbles can occur during these events and how these filter bubbles can potentially lead to intolerance in some cases. The data provided by Facebook Tracking Exposed will then be combined with information from interviews and existing information regarding the topic to create a thorough analysis of the ways Facebook filter bubbles may have led to influencing in/interfering with the presidential elections in the US.
When discussing this problem, there are multiple factors that play a role. For instance, the ignorance of social media users when it comes to curation by Facebook, maybe bigger than you think. According to a 2015 study conducted by Eslami et al., more than 60% of Facebook users are unaware of any filtering at all on the platform. They believe that every story and picture that either is being shared by friends or pages, will show on their newsfeed.
We aim to interview a person who has extensive knowledge of filter bubbles and their socio-political effects. It would, therefore, be ideal to interview Eli Pariser, the author of “The Filter Bubble: What the Internet Is Hiding From You.”, where he coined the term ‘filter bubble’. There is a contact page on his website so we hope that he agrees to a Skype call interview. Alternatively, he could perhaps answer a few questions via email. If not, we will try to find someone else with similar expertise.
#1: To what extent do you think that filter bubbles will influence the voter’s decision when it comes to the presidential election of 2020?
#2: Are there any measures taken to either counter or support this so-called phenomenon? If yes, what are they?
#3: Do you think that politicians are abusing users’ filter bubbles to steer them into voting for them?
#4: We are using a tool called Facebook Tracking Exposed, which tracks your activity on Facebook. With the use of two fake accounts, we are trying to map the filter bubbles that occur using Facebook. Do you think that this tool would be able to map this phenomenon regarding the matter?
#5: Have you had any experiences or findings regarding the U.S. presidential elections and filter bubbles?
#6: Do you think that there might be a shift to online campaigning using filter bubbles as a political weapon in the future?
‘Facebook Tracking Exposed’. n.d. Facebook Tracking Exposed. Accessed 19 February 2020. https://facebook.tracking.exposed/.
‘What We Collect | Facebook Tracking Exposed’. n.d. Facebook Tracking Exposed. Accessed 19 February 2020. https://facebook.tracking.exposed/privacy/.
Eslami, Motahhare et al. 2015. “I always assumed that I wasn’t really that close to [her]”: Reasoning about invisible algorithms in the news feed” University of Illinois at Urbana-Champaign.