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Echo Chambers and Audio Signal Processing

Published online by Cambridge University Press:  30 September 2020

Benjamin Elzinga*
Affiliation:
Georgetown University, Washington DC, USA
*
*Corresponding author. Email: be72@georgetown.edu
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Abstract

Following Cass Sunstein's popular treatment of the concept, echo chambers are often defined as environments which exclude contrary opinions through omission. C. Thi Nguyen contests the popular usage and defines echo chambers in terms of in-group trust and out-group distrust. In this paper, I argue for a more comprehensive treatment. While both exclusion by omission and out-group distrust help sustain echo chambers, neither defines the phenomenon. I develop a social network model of echo chambers which focuses on the role of belief-reinforcing echoes. First, I argue that the model allows us to incorporate Nguyen's main point about distrust without construing other commentators as deeply mistaken about the nature of echo chambers. Second, I use the model to develop an account of collaborative resistance and use it to clarify the role echo chambers play in spreading misinformation.

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Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press
Figure 0

Figure 1. A partial representation of a social network in action.

Figure 1

Figure 2. An enriched representation of a social network. Nodes in the center and on the right are cut off from nodes on the left by means of various filters. Belief expressions may be blocked (represented by black dots) by a subtractive filter or prevented from significantly impacting one's belief in the expressed content by an all-pass filter (it may nevertheless have an effect on other beliefs, e.g., one's beliefs about what a distrusted agent believes). Belief expressions which get through (represented by black arrowheads) may help support, reinforce, or modify the agent's belief in the expressed content. Grey arrows representing available information channels are removed for the sake of simplicity, black arrows represent typical patterns of information flow, and filters are understood as applying only to incoming messages. The absence of a link between nodes is not intended to be significant.

Figure 2

Figure 3. An asymmetric media network. While disconfirming news stories from the center regularly flow to the left, the right selectively blocks disconfirming stories coming from the center. In the case of news media institutions, a black arrowhead penetrating to the center of the node represents an expressed content being reported as fact (or minimally reported as a piece of valuable evidence or testimony supporting a fact). A black dot on a dashed circle represents a claim being blocked by subtractive filters which determine whether a story is newsworthy in accordance with prevailing journalistic norms. While any news institution will attempt to exclude irrelevant or uninteresting stories, part of Benkler et al.'s claim is that the right-wing media also actively filters out identity-disconfirming stories to a greater extent than left-wing media.

Figure 3

Figure 4. Right-wing distrust amplification: when ideas pass through right-wing subtractive filters, they are typically blocked by credibility filters. Even if the right-wing media reports on the left, they do so in a way that expresses the idea that the left is not to be trusted.

Figure 4

Figure 5. A representation of the ‘propaganda pipeline’. While information travels freely from peripheral online platforms to the right-wing echo chamber, leftwing media views the right through a lens of distrust.