Purpose

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

Design/methodology/approach

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

Findings

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Originality/value

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.

中文翻译：

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深入研究分歧：对社交媒体上基于认知偏见的两极分化的系统回顾

目的

社交媒体在全球的盛行及其造成两极分化的潜力引起了激烈的争论和影响。以前的文献经常假设任何媒体的意识形态偏见对于两极分化过程来说都是静态的和外生的。通过从生态系统方法研究整个两极分化，作者旨在确定有助于减轻两极分化不利影响并促进更健康的在线话语的政策和策略。

设计/方法论/途径

为了调查在线两极分化，作者对大约 400 篇研究文章进行了系统回顾和分析，以探索认知偏差和两极分化之间的联系，检查因果证据和相关证据。作者广泛评估并整合了有关网络两极分化与公众参与、选择性曝光和政治民主等关键因素之间相关性的现有研究。在此基础上，作者开发了一个 PolarSphere 生态系统，用于捕获并说明在线极化形成的过程。

发现

作者的评论揭示了广泛的关联，包括意识形态认知、偏见、公众参与、错误信息和沟通不畅、政治民主、回音室和选择性暴露、异质性和信任。尽管偏见对社交媒体两极分化的影响取决于特定环境和内部/外部条件，但某些变量在多种背景下表现出很强的关联性。作者以这些观察结果为基础，构建了 PolarSphere（社交媒体上基于偏见的极化生态系统），对极化形成的过程进行了理论化。

原创性/价值

基于PolarSphere生态系统，作者认为，政府和民间社会保持警惕并投资于进一步的研究以深入理解认知偏见如何影响在线两极分化至关重要，这可能会找到消除两极分化的方法。