Are Filter Bubbles Real?

MC7019: Week 4 Blog

Four years ago when I was a sophomore at LSU, I was sitting in Dr. Porter's "Digital Brands" class, watching wide-eyed at Eli Pariser talk about "filter bubbles" in his famous 2011 TED Talk. That was the first time I had ever heard the term, and it genuinely blew my mind. He explained how and why the search results we get and news we read online are getting so personalized. Social media algorithms are putting us in information bubbles and preventing us from seeing viewpoints that we don't agree with - mostly without our awareness. It seems pretty self-evident that our social media feeds show us more of what we like and less of what we don't like, making it as "sticky" as possible and ultimately dividing our nation into a hyper-polarized society. But is that really the case? There are many skeptics who disagree with Pariser's technological determinist view.

https://www.youtube.com/watch?v=B8ofWFx525s

Axel Bruns' "Are Filter Bubbles Real?" exposes the flaws in the popular ideas of echo chambers and filter bubbles. He demonstrates how it's nearly impossible to completely separate from views outside of your own on social media, especially as context collapse actively prevents that from happening. In a typical newsfeed scroll, you'll see posts and pictures from high school friends, classmates, co-workers and your grandparents - all of whom have different views and perspectives on a variety of topics, not just on politics. And speaking of politics, political news are generally very minor interests in peoples lives and online networks. Saying that out feeds are filled with primarily political content is just not true, unless you're a politician or journalist. We mostly see information related to events of the day, what people are eating, whose birthday it is, engagement announcements, sports, music and so much more. Additionally, research shows that those on the wrong side of the digital divide actually tend to be more stuck in ideological isolation than those who are connected. The internet and social media are proven to give us a diverse set of information and make "serendipitous encounters with counter-attitudinal content more common."

By using evidence from empirical research, Bruns debunks the theses that echo chambers and filter bubbles create and cause highly fragmented divides in political ideologies. He puts it simply:

"We cannot absolve ourselves from the mess we are in by simply blaming technology."

Well, that burst my bubble. I was truly in the Pariser camp believing that filter bubbles and echo chambers were causing some, if not most, of the mess in our democracy today. How else could extreme Trump supporters, for example, get so caught up in the lies and misinformation that have been fueling their hyper-partisanship, leading them to violently storm Capitol Hill on Jan. 6, 2021? As someone who is studying mass communication and its limited effects , I understand that numerous factors outside of social media filter bubbles led up to that moment. However, I believed filter bubbles and echo chambers were the the straw that broke the camel's back. Bruns would argue that while fake news and misinformation surely were contributing factors to the extreme partisanship, most if not all of those rioters saw messages and information from mainstream media or sources that disagree with them because that information reinforced their own perspectives through confirmation bias.

Although I wish Bruns talked more about media platforms outside of Facebook and Twitter such as Instagram or Reddit, his overall argument applies to all these platforms as they serve as only a portion of the general public's media diet. To combat hyper-polarization, we as a society need to have a better understanding of how people take in information and what they do with that information. Understanding relationship networks, groupthink, conformity, confirmation bias and more may be the first step to breaking down how polarization occurs. Scholars of mass communication, political science, psychology and sociology need to continue to work together to understand why and how this happens, beyond social media. Don't let filter bubbles distract you from the real problem.