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arXiv · 1712.06009

Population polarization dynamics and next-generation social media algorithms

N. F. Johnson·P. Manrique·M. Zheng·Z. Cao·J. Botero·S. Huang·N. Aden·C. Song·J. Leady·N. Velasquez·E. M. Restrepo
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Abstract

We present a many-body theory that explains and reproduces recent observations of population polarization dynamics, is supported by controlled human experiments, and addresses the controversy surrounding the Internet's impact. It predicts that whether and how a population becomes polarized is dictated by the nature of the underlying competition, rather than the validity of the information that individuals receive or their online bubbles. Building on this framework, we show that next-generation social media algorithms aimed at pulling people together, will instead likely lead to an explosive percolation process that generates new pockets of extremes.

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N. F. Johnson, P. Manrique, M. Zheng, Z. Cao, J. Botero, S. Huang, N. Aden, C. Song, J. Leady, N. Velasquez, E. M. Restrepo. 2017-12-16. Population polarization dynamics and next-generation social media algorithms. https://arxiv.org/abs/1712.06009

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