A. Reina, T. Bose, V. Srivastava, J.A.R. Marshall

Royal Society Open Science 10: 230175, 2023.

It is usually assumed that information cascades are most likely to occur when an early but incorrect opinion spreads through the group. Here, we analyse models of confidence-sharing in groups and reveal the opposite result: simple but plausible models of naive-Bayesian decision-making exhibit information cascades when group decisions are synchronous; however, when group decisions are asynchronous, the early decisions reached by Bayesian decision-makers tend to be correct and dominate the group consensus dynamics. Thus early decisions actually rescue the group from making errors, rather than contribute to it. We explore the likely realism of our assumed decision-making rule with reference to the evolution of mechanisms for aggregating social information, and known psychological and neuroscientific mechanisms.

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Cristobal Pais, Jose Ramon Gonzalez-Olabarria, Pelagie Elimbi Moudio, Jordi Garcia-Gonzalo, Marta C. González & Zuo-Jun Max Shen
Communications Earth & Environment volume 4, Article number: 267 (2023)

Different interpretations of the fire regime concept have limited the capacity to allocate specific fire regimes worldwide. To solve this limitation, in this study, we present a framework to frame contemporary fire regimes spatially on a global scale. We process historical wildfire records between 2000 and 2018 across the six continents. We uncover 15 global pyromes with clear differences in fire-related metrics, such as frequency and size. The pyromes were further divided into 62 regimes based on spatial aggregation patterns. This spatial framing of contemporary fire regimes allows for an interpretation of how a combination of driving factors such as vegetation, climate, and demographic features can result in a specific fire regime. To the best of our knowledge, this open source platform at unprecedented scale expands on existing classification efforts and bridges the gaps between global and regional fire studies. A framework to classify fire regimes spatially on a global scale based on historical records between 2000 and 2018 reveals 15 global pyromes with differences in fire-related metrics and indicates how factors such as vegetation, climate, and demographic features can result in a specific fire regime.

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Niraj Kushwaha, Edward D Lee 
PNAS Nexus, Volume 2, Issue 7, July 2023, pgad228

Conflicts, like many social processes, are related events that span multiple scales in time, from the instantaneous to multi-year development, and in space, from one neighborhood to continents. Yet, there is little systematic work on connecting the multiple scales, formal treatment of causality between events, and measures of uncertainty for how events are related to one another. We develop a method for extracting causally related chains of events that addresses these limitations with armed conflict. Our method explicitly accounts for an adjustable spatial and temporal scale of interaction for clustering individual events from a detailed data set, the Armed Conflict Event & Location Data Project. With it, we discover a mesoscale ranging from a week to a few months and tens to hundreds of kilometers, where long-range correlations and nontrivial dynamics relating conflict events emerge. Importantly, clusters in the mesoscale, while extracted from conflict statistics, are identifiable with mechanism cited in field studies. We leverage our technique to identify zones of causal interaction around conflict hotspots that naturally incorporate uncertainties. Thus, we show how a systematic, data-driven, and scalable procedure extracts social objects for study, providing a scope for scrutinizing and predicting conflict and other processes.

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Milan Jović, Lovro Šubelj, Tea Golob, Matej Makarovič, Taha Yasseri, Danijela Boberić Krstićev, Srdjan Škrbić & Zoran Levnajić
Scientific Reports volume 13, Article number: 12451 (2023)

Terrorist attacks not only harm citizens but also shift their attention, which has long-lasting impacts on public opinion and government policies. Yet measuring the changes in public attention beyond media coverage has been methodologically challenging. Here we approach this problem by starting from Wikipedia’s répertoire of 5.8 million articles and a sample of 15 recent terrorist attacks. We deploy a complex exclusion procedure to identify topics and themes that consistently received a significant increase in attention due to these incidents. Examining their contents reveals a clear picture: terrorist attacks foster establishing a sharp boundary between “Us” (the target society) and “Them” (the terrorist as the enemy). In the midst of this, one seeks to construct identities of both sides. This triggers curiosity to learn more about “Them” and soul-search for a clearer understanding of “Us”. This systematic analysis of public reactions to disruptive events could help mitigate their societal consequences.

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