Worry over polarization has grown alongside the digital information consumption revolution. Where most scientific work considered user-generated and user-disseminated (i.e.,~Web 2.0) content as the culprit, the potential of purely increased access to information (or Web 1.0) has been largely overlooked. Here, we suggest that the shift to Web 1.0 alone could include a powerful mechanism of belief extremization. We study an empirically calibrated persuasive argument model with confirmation bias. We compare an offline setting -- in which a limited number of arguments is broadcast by traditional media -- with an online setting -- in which the agent can choose to watch contents within a very wide set of possibilities. In both cases, we assume that positive and negative arguments are balanced. The simulations show that the online setting leads to significantly more extreme opinions and amplifies initial prejudice.

翻译：随着数字信息消费革命的发展，人们对观点极化的担忧与日俱增。当前大多数科学研究将用户生成和传播的内容（即Web 2.0）视为罪魁祸首，而纯粹因信息获取渠道增加（即Web 1.0）所潜藏的极化可能性在很大程度上被忽视了。本文提出，仅向Web 1.0的转变就可能包含一种强有力的信念极端化机制。我们研究了一个经过经验校准的、具有确认偏见的说服性论证模型。我们比较了两种情景：离线情景——传统媒体传播的论点数量有限；在线情景——智能体可以在极其广泛的选项中选择观看内容。在这两种情景中，我们都假设正面和负面的论点数量均衡。模拟结果表明，在线情景会导致显著更极端的观点，并放大初始偏见。