Details

Autor(en) / Beteiligte

• Johnson, N. F.
• Leahy, R.
• Restrepo, N. Johnson
• Velasquez, N.
• Zheng, M.
• Manrique, P.
• Devkota, P.
• Wuchty, S.

Titel

Hidden resilience and adaptive dynamics of the global online hate ecology

Ist Teil von

• Nature (London), 2019-09, Vol.573 (7773), p.261-265

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2019

Quelle

MEDLINE

Beschreibungen/Notizen

• Online hate and extremist narratives have been linked to abhorrent real-world events, including a current surge in hate crimes 1 – 6 and an alarming increase in youth suicides that result from social media vitriol 7 ; inciting mass shootings such as the 2019 attack in Christchurch, stabbings and bombings 8 – 11 ; recruitment of extremists 12 – 16 , including entrapment and sex-trafficking of girls as fighter brides 17 ; 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 18 ; 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 19 , 20 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 21 , 22 such as financial fraud. The dynamics of interactions between hate-orientated networks on different online platforms is characterized, and a mathematical model predicts that policing on one online platform can make matters worse and generate ‘darker’ parts of the Internet.