论文标题
信息访问的悖论:建模社交媒体诱导的极化
The Paradox of Information Access: On Modeling Social-Media-Induced Polarization
论文作者
论文摘要
该论文在人类信念中开发了一种随机的漂移模型,表明当今的无访问信息量,再加上消费者的确认偏见和自然偏爱更偏远的内容,一定会导致两极分化。该模型解释了在增加共享年龄增长的意识形态碎片化的悖论。由于社交媒体,搜索引擎和其他实时信息共享渠道旨在促进信息的访问,因此由于随后的信息过载而出现了内容过滤的需求。通常,消费者选择与他们的个人观点和价值观相匹配的信息。当今的信息策划服务可以通过根据观察到的消费者偏好过滤新内容来最大程度地提高用户参与度来回应这种选择中固有的偏差。因此,个人暴露于越来越狭窄的意识形态谱系,从而使社会分裂成越来越多的意识形态孤立的飞地。我们将这种动态称为信息访问的悖论。该模型还表明,通过少量的置于良好的错误信息,可实现的损害不成比例。本文描述了建模方法,并评估了不同人口规模和参数设置的建模结果。
The paper develops a stochastic model of drift in human beliefs that shows that today's sheer volume of accessible information, combined with consumers' confirmation bias and natural preference to more outlying content, necessarily lead to increased polarization. The model explains the paradox of growing ideological fragmentation in the age of increased sharing. As social media, search engines, and other real-time information sharing outlets purport to facilitate access to information, a need for content filtering arises due to the ensuing information overload. In general, consumers select information that matches their individual views and values. The bias inherent in such selection is echoed by today's information curation services that maximize user engagement by filtering new content in accordance with observed consumer preferences. Consequently, individuals get exposed to increasingly narrower bands of the ideology spectrum, thus fragmenting society into increasingly ideologically isolated enclaves. We call this dynamic the paradox of information access. The model also suggests the disproportionate damage attainable with a small infusion of well-positioned misinformation. The paper describes the modeling methodology, and evaluates modeling results for different population sizes and parameter settings.