Rightfully-Placed Blame: How social media algorithms facilitate post-truth politics

Social media algorithms have facilitated post-truth politics in online spaces such as Facebook and Twitter. The personalisation mechanisms of recommender algorithms construct and trap people in filter bubbles facilitating a virality of misinformation, lowering scrutiny towards non-dominant information sources, and becoming a means in which malicious actors proliferate deliberately misinformative or biassed knowledge. Eli Pariser’s (2011) publication is the structural argument in which this paper’s claim is grounded in. Literature on post-truth scholarship agreeing with this claim is engaged to demonstrate how the personalisation mechanisms have facilitated post-truth politics with the echo chamber phenomena, which imbues cognitive biases that inhibit our ability to impartially engage with counter-attitudinal opinion. Echo chambers have been observed on Facebook and Twitter, particularly amongst conspiracists and during the 2016 US presidential election, and have been found to facilitate post-truth politics by enabling misinformation to run rampant and reducing trust in government authority, resulting in political polarisation. A particularly agency-based criticism towards the causal relationship between post-truth conditions and social media algorithms is explored and scrutinised, as embodied by Guess et al.’s (2018) publication addressing weaknesses of the ‘blame’ we place on social media algorithms for political problems within society. We conclude that social media algorithms facilitate post-truth politics regardless of the agency in which the politically-engaged and aware user may employ due to the difficulty of ‘leaving’ filter bubbles. Excessive expectation is further placed on the non-politically engaged majority, who are additionally ignorant of filter bubbles they may be trapped in.