arXiv subjects

P. Manrique

Publications and source records attributed to P. Manrique.

6 recordsLinked to original sources

arXiv2020

Covid-19 infodemic reveals new tipping point epidemiology and a revised $R$ formula

Many governments have managed to control their COVID-19 outbreak with a simple message: keep the effective '$R$ number' $R<1$ to prevent widespread contagion and flatten the curve. This raises the question whether a similar policy could control dangerous online 'infodemics' of information, misinformation and disinformation. Here we show, using multi-platform data from the COVID-19 infodemic, that its online spreading instead encompasses a different dynamical regime where communities and users within and across independent platforms, sporadically form temporary active links on similar timescales to the viral spreading. This allows material that might have died out, to evolve and even mutate. This has enabled niche networks that were already successfully spreading hate and anti-vaccination material, to rapidly become global super-spreaders of narratives featuring fake COVID-19 treatments, anti-Asian sentiment and conspiracy theories. We derive new tools that incorporate these coupled social-viral dynamics, including an online $R$, to help prevent infodemic spreading at all scales: from spreading across platforms (e.g. Facebook, 4Chan) to spreading within a given subpopulation, or community, or topic. By accounting for similar social and viral timescales, the same mathematical theory also offers a quantitative description of other unconventional infection profiles such as rumors spreading in financial markets and colds spreading in schools.

physics.soc-ph↗

arXiv2020

Hidden order in online extremism and its disruption by nudging collective chemistry

We show that the eclectic "Boogaloo" extremist movement that is now rising to prominence in the U.S., has a hidden online mathematical order that is identical to ISIS during its early development, despite their stark ideological, geographical and cultural differences. The evolution of each across scales follows a single shockwave equation that accounts for individual heterogeneity in online interactions. This equation predicts how to disrupt the onset and 'flatten the curve' of such online extremism by nudging its collective chemistry.

physics.soc-ph↗

arXiv2018

Social media cluster dynamics create resilient global hate highways

Online social media allows individuals to cluster around common interests - including hate. We show that tight-knit social clusters interlink to form resilient 'global hate highways' that bridge independent social network platforms, countries, languages and ideologies, and can quickly self-repair and rewire. We provide a mathematical theory that reveals a hidden resilience in the global axis of hate; explains a likely ineffectiveness of current control methods; and offers improvements. Our results reveal new science for networks-of-networks driven by bipartite dynamics, and should apply more broadly to illicit networks.

physics.soc-ph↗

arXiv2017

Population polarization dynamics and next-generation social media algorithms

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.

physics.soc-ph↗

arXiv2017

New Online Ecology of Adversarial Aggregates: ISIS and beyond

Support for extremist entities - whether from the far right, or far left - often manages to survive globally online despite significant external pressure, and may ultimately inspire violent acts by individuals having no obvious prior history of extremism. Examining longitudinal records of extremist online activity, we uncovered an ecology evolving on a daily timescale that drives online support, and we provide a mathematical theory that describes it. The ecology features self-organized aggregates (online groups such as on Facebook or another social media analog) that proliferate preceding the onset of recent real-world campaigns, and adopt novel adaptive mechanisms to enhance their survival. One of the predictions is that development of large, potentially potent online groups can be thwarted by targeting smaller ones.

physics.soc-ph↗

arXiv2017

Multiscale dynamical network mechanisms underlying aging from birth to death

How self-organized networks develop, mature and degenerate is a key question for sociotechnical, cyberphysical and biological systems with potential applications from tackling violent extremism through to neurological diseases. So far, it has proved impossible to measure the continuous-time evolution of any in vivo organism network from birth to death. Here we provide such a study which crosses all organizational and temporal scales, from individual components (10^1) through to the mesoscopic (10^3) and entire system scale (10^6). These continuous-time data reveal a lifespan driven by punctuated, real-time co-evolution of the structural and functional networks. Aging sees these structural and functional networks gradually diverge in terms of their small-worldness and eventually their connectivity. Dying emerges as an extended process associated with the formation of large but disjoint functional sub-networks together with an increasingly detached core. Our mathematical model quantifies the very different impacts that interventions will have on the overall lifetime, period of initial growth, peak of potency, and duration of old age, depending on when and how they are administered. In addition to their direct relevance to online extremism, our findings offer fresh insight into aging in any network system of comparable complexity for which extensive in vivo data is not yet available.

physics.soc-ph↗