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There is a contradiction at the heart of our current understanding of individual and collective mobility patterns. On the one hand, a highly infuential body of literature on human mobility driven by analyses of massive empirical datasets fnds that human movements show no evidence of characteristic spatial scales. There, human mobility is described as scale free 1–3 . On the other hand, geographically, the concept of scale—referring to meaningful levels of description from individual buildings to neighbourhoods, cities, regions and countries—is central for the description of various aspects of human behaviour, such as socioeconomic interactions, or political and cultural dynamics 4,5 . Here we resolve this apparent paradox by showing that day-to-day human mobility does indeed contain meaningful scales, corresponding to spatial 'containers' that restrict mobility behaviour. The scale-free results arise from aggregating displacements across containers. We present a simple model—which given a person's trajectory—infers their neighbourhood, city and so on, as well as the sizes of these geographical containers. We fnd that the containers—characterizing the trajectories of more than 700,000 individuals—do indeed have typical sizes. We show that our model is also able to generate highly realistic trajectories and provides a way to understand the diferences in mobility behaviour across countries, gender groups and urban–rural areas.

The global public sphere has changed dramatically over the past decades: A significant part of public discourse now takes place on algorithmically driven platforms. Despite its growing importance, there is scant large-scale academic research on the long-term evolution of user behaviour on these platforms. Here, we evaluate the behaviour of 600,000 individual Twitter users between 2012 and 2019 and find empirical evidence for a cohort-level acceleration of the way Twitter is used. Across time, we observe changing user-level behaviours: more tweets per time, denser interactions with others via retweets, and shorter content horizons, expressed as an individual's decaying autocorrelation of topics over time. We show that the change in usage patterns is not simply caused by a growing user base. While behaviour remains remarkably stable within each cohort over time, we relate these observations to changing compositions of new users with each new cohort containing increasingly active individuals. Our findings complement recent empirical work on social acceleration by tracking cohorts over time, controlling for cohort size, and analyzing their behavioural composition.

AbstractComplex networks have recently attracted much interest due to their prevalence in nature and our daily lives (Vespignani, 2009; Newman, 2010). A critical property of a network is its resilience to random breakdown and failure (Albert et al., 2000; Cohen et al., 2000; Callaway et al., 2000; Cohen et al., 2001), typically studied as a percolation problem (Stauffer & Aharony, 1994; Achlioptas et al., 2009; Chen & D'Souza, 2011) or by modeling cascading failures (Motter, 2004; Buldyrev et al., 2010; Brummitt, et al. 2012). Many complex systems, from power grids and the Internet to the brain and society (Colizza et al., 2007; Vespignani, 2011; Balcan & Vespignani, 2011), can be modeled using modular networks comprised of small, densely connected groups of nodes (Girvan & Newman, 2002). These modules often overlap, with network elements belonging to multiple modules (Palla et al. 2005; Ahn et al. 2010). Yet existing work on robustness has not considered the role of overlapping, modular structure. Here we study the robustness of these systems to the failure of elements. We show analytically and empirically that it is possible for the modules themselves to become uncoupled or non-overlapping well before the network disintegrates. If overlapping modular organization plays a role in overall functionality, networks may be far more vulnerable than predicted by conventional percolation theory.

Abstract
Smartphones have profoundly changed human life. Nevertheless, the factors that shape how we use our smartphones remain unclear, in part due to limited availability of usage-data. Here, we investigate the impact of a key environmental factor: users' exposure to urban and rural contexts. Our analysis is based on a global dataset describing mobile app usage and location for ∼500,000 individuals. We uncover strong and nontrivial patterns. First, we confirm that rural users tend to spend less time on their phone than their urban counterparts. We find, however, that individuals in rural areas tend to use their smartphones for activities such as gaming and social media. In cities, individuals preferentially use their phone for activities such as navigation and business. Are these effects (1) driven by differences between individuals who choose to live in urban vs. rural environments or do they (2) emerge because the environment itself affects online behavior? Using a quasi-experimental design based on individuals that move from the city to the countryside—or vice versa—we confirm hypothesis (2) and find that smartphone use changes according to users's environment. This work presents a quantitative step forward towards understanding how the interplay between environment and smartphones impacts human lives. As such, our findings could provide information to better regulate persuasive technologies embedded in smartphone apps. Further, our work opens the door to understanding new mechanisms leading to urban/rural divides in political and socioeconomic attitudes.

As courts strive to simultaneously remain self-consistent and adapt to new legal challenges, a complex network of of citations between decided cases is established. Using network science methods to analyze the underlying patterns of citations between cases can help us understand the large-scale mechanisms which shape the judicial system. Here, we use the case-to-case citation structure of the Court of Justice of the European Union to examine this question. Using a link-prediction model, we show that over time the complex network of citations evolves in a way which improves our ability to predict new citations. Investigating the factors which enable prediction over time, we find that the content of the case documents plays a decreasing role, whereas both the predictive power and significance of the citation network structure itself show a consistent increase over time. Finally, our analysis enables us to validate existing citations and recommend potential citations for future cases within the court.

As courts strive to simultaneously remain self-consistent and adapt to new legal challenges, a complex network of of citations between decided cases is established. Using network science methods to analyze the underlying patterns of citations between cases can help us understand the large-scale mechanisms which shape the judicial system. Here, we use the case-to-case citation structure of the Court of Justice of the European Union to examine this question. Using a link-prediction model, we show that over time the complex network of citations evolves in a way which improves our ability to predict new citations. Investigating the factors which enable prediction over time, we find that the content of the case documents plays a decreasing role, whereas both the predictive power and significance of the citation network structure itself show a consistent increase over time. Finally, our analysis enables us to validate existing citations and recommend potential citations for future cases within the court.

As courts strive to simultaneously remain self-consistent and adapt to new legal challenges, a complex network of of citations between decided cases is established. Using network science methods to analyze the underlying patterns of citations between cases can help us understand the large-scale mechanisms which shape the judicial system. Here, we use the case-to-case citation structure of the Court of Justice of the European Union to examine this question. Using a link-prediction model, we show that over time the complex network of citations evolves in a way which improves our ability to predict new citations. Investigating the factors which enable prediction over time, we find that the content of the case documents plays a decreasing role, whereas both the predictive power and significance of the citation network structure itself show a consistent increase over time. Finally, our analysis enables us to validate existing citations and recommend potential citations for future cases within the court.

Evidence links greenspace exposure with restorative benefits to cognition and well-being, yet nature contact is declining for younger demographics. Although natural settings have been shown to restore the capacity to inhibit distracting stimuli, it remains unknown whether smartphone attention capture disrupts nature contact. Here, we analyzed ~2.5 million observations of logged smartphone use, texting, calling, and environmental exposures for 701 young adults over 2 years. Participants' weekly smartphone screen-time was over double their green-time. The relationship between greenspace exposure and smartphone activity differed by exposure dose, type, and mobility state. Calling and texting increased during short recreational greenspace visits while all smartphone use declined over the first 3 hr in nature areas, suggesting that nature exposure may support digital impulse inhibition. Those with elevated baseline screen-time or green-time significantly reduced device use in nature, indicating that parts of the biosphere may provide a reprieve from the cybersphere for highly connected youth.

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years-the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.

How should health authorities communicate to motivate the public to comply with health advice during a prolonged health crisis such as a pandemic? During the SARS-CoV-2 pandemic, for example, people have had to comply with successive restrictions as the world faced multiple races between controlling new waves of the virus and the development and implementation of vaccines. Here, we examine how health authorities and governments most effectively motivate the public by focusing on a specific race: between the Alpha variant and the implementation of the first generation of COVID-19 vaccinations in the winter of 2021. Following prior research on crisis communication, we focus on appeals to fear and hope using communicative aids in the form of visualizations based on epidemiological modelling. Using a population-based experiment conducted in United States ([Formula: see text] ), we demonstrate that a hope-oriented visual communication aid, depicting the competing effects on the epidemic curve of (1) a more infectious variant and (2) vaccinations, motivates public action more effectively than a fear-oriented visual communication, focusing exclusively on the threat of the new variant. The importance of the implementation of such hope-oriented messages is further highlighted by cross-national representative surveys from eight countries ([Formula: see text] ), which demonstrate that feelings of fear towards the Alpha variant alone were insufficient to activate strong compliance. Overall, these findings provide general insights into the importance of hope as a health communication strategy during the COVID-19 pandemic and beyond.

How should health authorities communicate to motivate the public to comply with health advice during a prolonged health crisis such as a pandemic? During the SARS-CoV-2 pandemic, for example, people have had to comply with successive restrictions as the world faced multiple races between controlling new waves of the virus and the development and implementation of vaccines. Here, we examine how health authorities and governments most effectively motivate the public by focusing on a specific race: between the Alpha variant and the implementation of the first generation of COVID-19 vaccinations in the winter of 2021. Following prior research on crisis communication, we focus on appeals to fear and hope using communicative aids in the form of visualizations based on epidemiological modelling. Using a population-based experiment conducted in United States (N= 3 , 022), we demonstrate that a hope-oriented visual communication aid, depicting the competing effects on the epidemic curve of (1) a more infectious variant and (2) vaccinations, motivates public action more effectively than a fear-oriented visual communication, focusing exclusively on the threat of the new variant. The importance of the implementation of such hope-oriented messages is further highlighted by cross-national representative surveys from eight countries (N= 3 , 995), which demonstrate that feelings of fear towards the Alpha variant alone were insufficient to activate strong compliance. Overall, these findings provide general insights into the importance of hope as a health communication strategy during the COVID-19 pandemic and beyond.

How should health authorities communicate to motivate the public to comply with health advice during a prolonged health crisis such as a pandemic? During the SARS-CoV-2 pandemic, for example, people have had to comply with successive restrictions as the world faced multiple races between controlling new waves of the virus and the development and implementation of vaccines. Here, we examine how health authorities and governments most effectively motivate the public by focusing on a specific race: between the Alpha variant and the implementation of the first generation of COVID-19 vaccinations in the winter of 2021. Following prior research on crisis communication, we focus on appeals to fear and hope using communicative aids in the form of visualizations based on epidemiological modelling. Using a population-based experiment conducted in United States ([Formula: see text]), we demonstrate that a hope-oriented visual communication aid, depicting the competing effects on the epidemic curve of (1) a more infectious variant and (2) vaccinations, motivates public action more effectively than a fear-oriented visual communication, focusing exclusively on the threat of the new variant. The importance of the implementation of such hope-oriented messages is further highlighted by cross-national representative surveys from eight countries ([Formula: see text]), which demonstrate that feelings of fear towards the Alpha variant alone were insufficient to activate strong compliance. Overall, these findings provide general insights into the importance of hope as a health communication strategy during the COVID-19 pandemic and beyond.