假新闻：不封禁，不传播——通过隔离机制
Fake news: No ban, No spread -- with Sequestration
AI总结：
本文提出“不封禁，不传播——通过隔离机制”的假新闻治理新途径，利用Galam模型分析发现并重塑特殊参数下的社会几何景观，实现言论自由与假新闻影响的自然隔离中和。
摘要：
假新闻如今是自由和民主的公共舆论形成的重大威胁。为了遏制其传播，机构和政策制定者所采取的所有努力主要依赖于施加限制、禁止和事实核查网站，这最终导致对言论自由的有效限制。这种得到广泛共识的禁止政策，最近被 Elon Musk 应用于监管社交媒体 X 的争议性政策所打破，并引发了指责他宣扬仇恨言论的强烈反弹。在此，尽管存在上述两种政策，我探索了另一条途径，称为“不封禁，不传播——通过隔离机制”，这相当于在同时保留充分的言论自由和中和假新闻影响。为了调查我提案的可行性，我在 Galam 舆论动力学模型框架内处理该问题。除了模型的基本要素外，我首次探索了偏见打破平局和逆向行为同时激活对舆论动力学的影响。结果表明，确实大多数假新闻不会传播到小群体人群之外，因此不会构成全球性威胁。然而，我揭示了一些特殊的参数集，对于这些参数集，假新闻即使最初仅由少数几个智能体共享，也会“自然地”传播以入侵整个社区且毫无阻力。基于这些发现，我能够勾勒出一条路径，通过“自然地”阻断其传播来中和此类入侵性假新闻，有效地将其隔离在非常小的人群社交网络中。该方案依赖于重塑假新闻演化所在的社会几何景观。不需要任何禁止措施，假新闻被留作自由发展但被隔离。下一个具有挑战性的步骤将是设计措施，将模型的发现实施到社交媒体的现实世界中。
英文摘要：
Fake news is today a major threat to free and democratic making of public opinion. To curb their spread, all efforts by institutions and policy makers rely mainly on imposing restriction, prohibition and fact checking sites, which end up to an effective limitation of freedom of speech. This policy of prohibition, supported by a wide consensus, has been recently broken by the controversial policy applied by Elon Musk to regulate the social media X, with a backlash accusing him of promoting hate speech. Here, notwithstanding these two policies, I explore another avenue denoted ``No ban, No spread - with Sequestration", which amounts at the same time preserving full freedom of speech and neutralization of fake news impact. To investigate the feasibility of my proposal, I tackle the issue within the Galam model of opinion dynamics. In addition to the basic ingredients of the model, I explore for the first time the effect on the dynamics of opinion of a simultaneous activation of prejudice tie breaking and contrarian behavior. The results show that indeed most pieces of fake news do not propagate beyond small groups of people and thus pose no global threat. However, I have unveiled some peculiar sets of parameters for which fake news, even if initially shared by only a handful of agents, spreads ``naturally" to invade a whole community with no resistance. Based on these findings, I am able to outline a path to neutralize such invasive fake news by blocking "naturally" its spread, effectively sequestering it in very small social networks of people. The scheme relies on reshaping the social geometry of the landscape in which fake news evolves. No prohibition is required with fake news left free to prosper but being sequestrated. Next challenging step will be designing measures to implement the model's findings into the real world of social media.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
