论文标题
意见动力学模型的合奏，以了解未定的在疫苗接种辩论中的作用
Ensemble of Opinion Dynamics Models to Understand the Role of the Undecided in the Vaccination Debate
论文作者
论文摘要
我们提出了三种模型，用于描述pro-vax和no-vax派系对未定的人群的招募。从Facebook页面的现实数据开始，我们比较了三种观点动态模型，这些模型捕获了未定人群的不同行为。 第一个是SIS模型的变体，其中未定的位置被认为无动于衷。中性人物可以被两个极端派系之一“感染”，加入他们的身边，当他们对辩论失去兴趣并恢复中立时，他们会“恢复”。 第二个模型是三方选民模型：中立页面代表中间派立场。他们倾向于他们的原始想法，这些想法与其他各方不同。 最后一个是适合疫苗接种辩论的双语模型：中性个体与亲抗Vax派别的群体一致，并且在极端之间具有妥协的位置（“双语主义”）。如果他们有一个单方面的社区，那么与双方的方便相同，并且双方都同意双方，而双重的人都会出现单语言主义者，可以成为单声道。 我们的结果描述了这三种模型之间的一致性：反vax意见传播的范围超过了亲vax，这要归功于在线社交网络中的初步战略立场（即使它们从较小的人口开始）。尽管大多数Pro-Vaccines节点在自己的社区中被隔离，但No-vaccines的节点被纠缠在大多数未确定的人群所在的网络的核心上。 In the last section, we propose and compare some policies that could be applied on the network to prevent anti-vax overcome: they lead us to conclude that censoring strategies are not effective, as well as segregating scenarios based on unfollowing decisions, while the addition of links in the network favours the containment of the pro-vax domain, reducing the distance between pro-vaxxers and undecided population.
We present three models used to describe the recruitment of the undecided population by pro-vax and no-vax factions. Starting from real-world data of Facebook pages, we compare three opinion dynamics models that catch different behaviours of the undecided population. The first one is a variation of the SIS model, where undecided position is considered indifferent. Neutrals can be "infected" by one of the two extreme factions, joining their side, and they "recover" when they lose interest in the debate and go back to neutrality. The second model is a three parties Voters model: neutral pages represent a centrist position. They lean their original ideas, that are different from both the other parties. The last is the Bilingual model adapted to the vaccination debate: neutral individuals are in agreement with both pro-, ad anti-vax factions, with a position of compromise between the extremes ("bilingualism''). If they have a one-sided neighbourhood, the convenience to agree with both parties comes out, and bi-linguists can become mono-linguists. Our results depicts an agreement between the three models: anti-vax opinion propagates more than pro-vax, thanks to an initial strategic position in the online social network (even if they start with a smaller population). While most of the pro-vaccines nodes are segregated in their own communities, no-vaccines ones are entangled at the core of the network, where the majority of undecided population is located. In the last section, we propose and compare some policies that could be applied on the network to prevent anti-vax overcome: they lead us to conclude that censoring strategies are not effective, as well as segregating scenarios based on unfollowing decisions, while the addition of links in the network favours the containment of the pro-vax domain, reducing the distance between pro-vaxxers and undecided population.
