Depolarization of echo chambers by random dynamical nudge

Currin, Christopher; Vera, Sebastián Vallejo; Khaledi-Nasab, Ali

doi:10.1038/s41598-022-12494-w

Cited by 13 publications

(5 citation statements)

References 61 publications

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“…Our proposed approach may empower users and ensure they are not trapped in echo chambers for specific content categories. 'Random nudges' could also expose the user to diverse views to reduce polarization 34 .…”

Section: Discussionmentioning

confidence: 99%

Reducing Echo Chamber Effects: An Allostatic Regulator for Recommendation Algorithms

Henry,

Pedersen,

Williams

et al. 2023

Preprint

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Recommendation systems are prevalent on the Internet but are prone to feedback loops that cause ‘echo chamber’ effects. We present an allostatic regulator for recommendation systems based on opponent process theory and behavioral posology principles to combat these effects. When applied as a code wrapper to a supervised K-Nearest Neighbors algorithm for movie recommendations, our prototype algorithm can dynamically restrict the proportion of potentially harmful content recommended to users. This technique is adaptable to other domains and is scalable to more complex machine learning algorithms with minimal changes to their internal parameters. Combining allostatic regulation with insights from human-derived models on the healthy limits of digital content consumption may provide app developers with a flexible tool to help users regulate their online experiences. In turn, allostatic regulation moderates positive feedback loops, potentially reducing echo chamber effects while increasing the transparency and interpretability of machine learning models.

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Section: Discussionmentioning

confidence: 99%

Reducing Echo Chamber Effects: An Allostatic Regulator for Recommendation Algorithms

Henry,

Pedersen,

Williams

et al. 2023

Preprint

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“…2) Structural component (Fig. 1B): More recent approaches have emphasized the role of social connections, and especially homophily, i.e., the connections between like-minded individuals (23,(53)(54)(55)(56). If there is no community structure, then there is no opinion homophily, and each individual is connected and therefore exposed to many different views.…”

Section: Definitionmentioning

confidence: 99%

Quantifying ideological polarization on a network using generalized Euclidean distance

2023

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An intensely debated topic is whether political polarization on social media is on the rise. We can investigate this question only if we can quantify polarization, by taking into account how extreme the opinions of the people are, how much they organize into echo chambers, and how these echo chambers organize in the network. Current polarization estimates are insensitive to at least one of these factors: They cannot conclusively clarify the opening question. Here, we propose a measure of ideological polarization that can capture the factors we listed. The measure is based on the generalized Euclidean distance, which estimates the distance between two vectors on a network, e.g., representing people’s opinion. This measure can fill the methodological gap left by the state of the art and leads to useful insights when applied to real-world debates happening on social media and to data from the U.S. Congress.

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“…Some echo chambers promote boundary spanning, some focus on broadly popular topics, some emphasise reputation building, and some relate to locally popular phenomena (Lee, Britt, and Kanthawala 2022). People share articles with similar views and track communities with the same stance as their own, resulting in group polarisation (Currin, Vera, and Khaledi-Nasab 2022). Social media users may exhibit highly prominent and polarised behaviours (Kubin and von Sikorski 2021), and politically mobilising messages strengthen the echo chambers (Jarvis 2010).…”

Section: Political Orientation and Echo Chambersmentioning

confidence: 99%

Determinants of the backfire effect: Discrepancies between two groups with different political orientations

Kang,

Liang

2023

InfTars

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In this study, we explored the determinants of the backfire effect by analysing supporters’ reactions to information propagated by the opposition camps. We focused on the topic of pork consumption. The study cohort (N = 971) comprised the supporters of the pan-blue (N = 422) and pan-green (N = 549) camps in Taiwan. Data were collected through an online survey. The echo chambers and message response emerged as robust factors influencing the backfire effect on individuals regardless of their political orientation. Message presentation negatively affected the induction of backfire effects. For the pan-green supporters, behavioural control and animal welfare attitude, respectively, exerted positive and negative influences on the induction of backfire effects. Our findings provide insights into the determinants of the backfire effect, a phenomenon wherein individuals fail to differentiate between fact and fiction despite receiving credible corrective information.

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Depolarization of echo chambers by random dynamical nudge

Cited by 13 publications

References 61 publications

Reducing Echo Chamber Effects: An Allostatic Regulator for Recommendation Algorithms

Reducing Echo Chamber Effects: An Allostatic Regulator for Recommendation Algorithms

Quantifying ideological polarization on a network using generalized Euclidean distance

Determinants of the backfire effect: Discrepancies between two groups with different political orientations

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