Physics Department, George Washington University, Washington, DC, USA.
Elliot School of International Affairs, George Washington University, Washington, DC, USA.
Nature. 2019 Sep;573(7773):261-265. doi: 10.1038/s41586-019-1494-7. Epub 2019 Aug 21.
Online hate and extremist narratives have been linked to abhorrent real-world events, including a current surge in hate crimes and an alarming increase in youth suicides that result from social media vitriol; inciting mass shootings such as the 2019 attack in Christchurch, stabbings and bombings; recruitment of extremists, including entrapment and sex-trafficking of girls as fighter brides; threats against public figures, including the 2019 verbal attack against an anti-Brexit politician, and hybrid (racist-anti-women-anti-immigrant) hate threats against a US member of the British royal family; and renewed anti-western hate in the 2019 post-ISIS landscape associated with support for Osama Bin Laden's son and Al Qaeda. Social media platforms seem to be losing the battle against online hate and urgently need new insights. Here we show that the key to understanding the resilience of online hate lies in its global network-of-network dynamics. Interconnected hate clusters form global 'hate highways' that-assisted by collective online adaptations-cross social media platforms, sometimes using 'back doors' even after being banned, as well as jumping between countries, continents and languages. Our mathematical model predicts that policing within a single platform (such as Facebook) can make matters worse, and will eventually generate global 'dark pools' in which online hate will flourish. We observe the current hate network rapidly rewiring and self-repairing at the micro level when attacked, in a way that mimics the formation of covalent bonds in chemistry. This understanding enables us to propose a policy matrix that can help to defeat online hate, classified by the preferred (or legally allowed) granularity of the intervention and top-down versus bottom-up nature. We provide quantitative assessments for the effects of each intervention. This policy matrix also offers a tool for tackling a broader class of illicit online behaviours such as financial fraud.
网络仇恨和极端主义叙事与令人憎恶的现实世界事件有关，包括仇恨犯罪的激增，以及社交媒体仇恨导致的青年自杀率令人震惊地上升；煽动大规模枪击事件，如 2019 年克赖斯特彻奇袭击事件、刺伤和爆炸事件；极端分子的招募，包括诱骗女孩作为战斗新娘进行性交易和人口贩卖；对公众人物的威胁，包括 2019 年对反脱欧政治家的口头攻击，以及对美国英国王室成员的混合（种族主义-反女性-反移民）仇恨威胁；以及与支持奥萨马·本·拉登的儿子和基地组织有关的 2019 年后 ISIS 时代的反西方仇恨的死灰复燃。社交媒体平台似乎在与网络仇恨的斗争中败下阵来，迫切需要新的见解。在这里，我们表明理解网络仇恨的弹性的关键在于其全球网络网络动态。互联的仇恨集群形成全球“仇恨高速公路”，借助集体在线适应能力，跨越社交媒体平台，有时甚至在被禁止后使用“后门”，以及在国家、大陆和语言之间跳跃。我们的数学模型预测，在单一平台（如 Facebook）内进行监管可能会使情况变得更糟，并最终在全球范围内产生“黑暗池”，在这些池内，网络仇恨将蓬勃发展。我们观察到当前的仇恨网络在受到攻击时会迅速在微观层面上重新布线和自我修复，这种方式类似于化学中形成共价键的方式。这种理解使我们能够提出一个政策矩阵，该矩阵可以帮助击败网络仇恨，根据干预的首选（或合法允许）粒度以及自上而下与自下而上的性质进行分类。我们对每种干预措施的效果进行了定量评估。该政策矩阵还为打击更广泛的一类非法在线行为（如金融欺诈）提供了一种工具。
