The spread of ideas in online social networks is a crucial phenomenon to understand nowadays the proliferation of fake news and their impact in democracies. This makes necessary to use models that mimic the circulation of rumors. The law of large numbers as well as the probability distribution of contact groups allow us to construct a model with a minimum number of hypotheses. Moreover, we can analyze with this model the presence of very polarized groups of individuals (humans or bots) who spread a rumor as soon as they know about it. Given only the initial number of individuals who know any news, in a population connected by an instant messaging application, we first deduce from our model a simple function of time to study the rumor propagation. We then prove that the polarized groups can be detected and quantified from empirical data. Finally, we also predict the time required by any rumor to reach a fixed percentage of the population.

中文翻译：

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不加批判的两极分化群体：在社交网络中将假新闻作为事实传播的影响

在线社交网络中思想的传播是了解当今假新闻泛滥及其对民主国家的影响的关键现象。这使得有必要使用模仿谣言传播的模型。大数定律以及接触组的概率分布使我们能够构建具有最少假设数量的模型。此外，我们可以用这个模型分析非常两极分化的个人（人类或机器人）群体的存在，他们一知道谣言就会散播。在通过即时消息应用程序连接的人群中，仅给定知道任何新闻的初始个体数量，我们首先从我们的模型中推导出一个简单的时间函数来研究谣言传播。然后我们证明可以从经验数据中检测和量化极化组。最后，