Computational Social Science

A study shows that, although the number of incarcerated people in the USA decreased during the first year of the COVID-19 pandemic, the fraction of incarcerated Black and Latino individuals increased.

Long conversations online consistently exhibit higher toxicity, yet toxic language does not invariably discourage people from participating in a conversation, and toxicity does not necessarily escalate as discussions evolve.

Difference-in-differences analysis indicates that the decision by Twitter to deplatform 70,000 users following the events at the US Capitol on 6 January 2021 had wider effects on the spread of misinformation.

We find that gender bias is more prevalent in images than text, that the underrepresentation of women online is substantially worse in images and that googling for images amplifies gender bias in a person’s beliefs.

Searching online to evaluate the truthfulness of false news articles increases the probability of believing the false news articles.

Analysis of research articles and patent applications shows that members of teams that collaborate remotely are less likely to make breakthrough discoveries than members of on-site teams.

There is extreme socioeconomic segregation in large US cities, arising from a greater choice of differentiated spaces targeted to specific socioeconomic groups, which can be countered by positioning city hubs (such as shopping centres) to bridge diverse neighbourhoods.

A large-scale field intervention experiment on 23,377 US Facebook users during the 2020 presidential election shows that reducing exposure to content from like-minded social media sources has no measurable effect on political polarization or other political attitudes and beliefs.

Ecologically valid data collected during the 2018 and 2020 US elections show that exposure to and engagement with partisan or unreliable news on Google Search are driven not primarily by algorithmic curation but by users’ own choices.

A decline in disruptive science and technology over time is reported, representing a substantive shift in science and technology, which is attributed in part to the reliance on a narrower set of existing knowledge.

Evolutionary multiplayer games in structured populations illustrate a variety of phenomena in natural and social systems. This research provides a mathematical framework to analyze multiplayer games with an arbitrary number of strategies on regular graphs.

Yu and colleagues leverage population-level data to construct a large-scale, geographically defined, inter-household social network. Using a multilevel network model, they show that having social ties in close geographic proximity is associated with stable household asset conditions, while geographically distant ties correlate to changes in asset allocation. Notably, they find that localised network interactions are associated with an increase in wealth inequality at the regional level, demonstrating how macro-level inequality may arise from micro-level social processes.

Informal transportation services constitute the primary form of public transport in the Global South. Here, the authors analyze the structure of route networks in cities across the globe, showing how informal routes self-organize into consistent line services that often outperform centralized services in the Global North, exhibiting fewer detours and comparable interconnectivity.

Educational environment is known to influence learning efficiency of students, however qualitative analysis of this effect has open questions. The authors propose a model to quantify roommate peer effects based on student accommodation distribution and their academic performance.

Zhao P.J. and his colleagues uncover spatial directionality of urban mobility by using new metrics of anisotropy and centripetality. They find monocentric cities have longer commutes with city expansion, while polycentric cities maintain consistent commuting patterns.

Thurner and colleagues explore how economic shocks spread risk through the globalized economy. They find that rich countries expose poor countries stronger to systemic risk than vice-versa. The risk is highly concentrated, however higher risk levels are not compensated with a risk premium in GDP levels, nor higher GDP growth. The findings put the often-praised benefits for developing countries from globalized production in a new light, by relating them to risks involved in the production processes

Collective cooperation is found across many social and biological systems. Here, the authors find that infrequent hub updates promote the emergence of collective cooperation and develop an algorithm that optimises collective cooperation with update rates.

Using large-scale mobility data, the authors examine how the quality of food in mobile environments away from home affects food choice.

Extracting scientific data from published research is a complex task required specialised tools. Here the authors present a scheme based on large language models to automatise the retrieval of information from text in a flexible and accessible manner.

Global research has identified six critical transformations to achieve the Sustainable Development Goals by 2030. Here, Allen et al model all six transformations in a national context and discuss implications for accelerating progress on the goals.

Authors of scientific papers are generally discouraged from citing works that had no direct influence on their research. This paper uses simulations to show that such rhetorical citations may have underappreciated effects on the scientific community, such as deconcentrating attention away from already highly-cited papers.

While federated learning is promising for efficient collaborative learning without revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high communication overhead, and struggles to adapt to heterogeneous models. Here, the authors show a federated distillation method to tackle these challenges, which leverages the strengths of knowledge distillation in a federated learning setting.

Second-person pronouns, such as “you” and “yours”, are common in human communication. Here, the authors show that in peer review, authors who address reviewers with second person pronouns receive fewer questions, shorter responses, and more positive feedback.

Social networks often segregate based on political identities. We show that such segregation is reduced when people know how others behave towards those from their outgroup and ingroup

Discovering innovative ideas from numerous candidates is hard. Here, the authors show that simple autonomous agents (AI bots) can facilitate creative semantic discovery in human groups by leveraging the wisdom of crowds, essentially reducing noise.

Social learning facilitates adaptive behaviour, yet people engage in it to varying degrees. Here, the authors use simulations to show how this variation can stem from flexible strategies that evolve if the benefits of social learning are uncertain.

Implicit biases are influenced by social contexts which, in cities, are shaped by the constraints of urban infrastructure networks. Here the authors show that more populous, more diverse, and less segregated cities are less biased and that this is predicted by a complex systems model.

Recent research shows the existence of outside individual options may hinder group collaboration. Here, the authors show that, when group boundaries are not fixed ex-ante, they facilitate collaboration via the formation of more optimistic groups.

Individual decisions drive the dynamics of collective systems. Here, the authors use an immersive-reality experiment to show that group incentives reduce social information use and improve performance in naturalistic collectives.

Here, using hypergraph modeling the authors show that surprising research (in terms of unexpected combinations of research contents and contexts) is associated with impact and arises from scientific outsiders solving problems in distant disciplines.

Cooperation is more likely when individuals can choose their interaction partner. However, here, the authors show that partner choice can increase resource inequality in a public goods game when people differ in resources and productivity needed for cooperation.

Mobile phone data reveals a significant decrease in the income diversity of urban encounters during the COVID-19 pandemic in the USA, even though overall mobility returned to pre-pandemic levels by late 2021. This was mainly due to persistent behavioral changes including less willingness to explore new places.

This study introduces a method to quantify trade in digital products, like cloud computing and mobile games. It finds that this trade grows rapidly, may impact trade balances, support economic decoupling, and enhance economic complexity measures.

Building data is needed for assessing progress towards urban Sustainable Development Goals. An international team of scientists studies the spatial distribution of buildings in all cities globally and unveils their uneven coverage in OpenStreetMap.

While large-scale GPS ___location datasets have been instrumental to applications in epidemiology, there are still several challenges with these data that should be considered and addressed to make data-driven epidemiology more reliable.

This paper introduces an algorithm to uncover laws of skill acquisition from naturally occurring data. By combining deep learning and symbolic regression, it accurately identifies cognitive states and extracts algebraic equations.

Using registry data from Denmark, Lehmann et al. create individual-level trajectories of events related to health, education, occupation, income and address, and also apply transformer models to build rich embeddings of life-events and to predict outcomes ranging from time of death to personality.

Zhi Liu et al. develop a method to measure disparities in reporting delays in urban crowdsourcing systems, uncovering socioeconomic disparities and providing actionable insights for interventions that enhance the efficiency and equity of city services.

Progress towards universal access to safe drinking water and nutritious food has been moving forward at a slower than desired rate. Computational tools can help accelerate progress towards these goals, but solutions need to be open source, and designed, developed and implemented in a participatory manner.

A graph-based artificial intelligence model for urban planning outperforms human-designed plans in objective metrics, offering an efficient and adaptable collaborative workflow for future sustainable cities.

Social media and other internet platforms are making it even harder for researchers to investigate their effects on society. One way forward is user-sourced data collection of data to be shared among many researchers, using robust ethics tools to protect the interests of research participants and society.

The study presents a mobility centrality index to delineate urban dynamics in quasi-real time with mobile-phone data. The results indicate that urban structures were becoming more monocentric during the COVID-19 lockdown periods in major cities in Spain.

The field of human mobility has evolved drastically in the past 20 years. In this Perspective, the authors discuss three key areas in human mobility, framed as minds, societies and algorithms, where they expect to see substantial improvements in the future.

Cities offer higher wages and more opportunities for adults but provide limited upward income mobility for children. This study finds that movement around cities varies more among US students of different income levels than among students and adults. Students from higher-income families spend more time outside the home and explore more unique locations, suggesting urban income mobility echoes physical mobility.

This study analyzes the influence of density on COVID-19 infection rates in cities across the United States and their relationship with socio-spatial inequalities. Its main finding is that density has a nonlinear relationship with infection rates and that socioeconomic factors influence mitigating behaviors in neighborhoods.

Workers’ skills shape their job opportunities and where they live, thus making skills a vital part of understanding cities and their economy. Modeling urban labor markets as occupation networks, this study finds that more-specific skill information better predicts career mobility and that workers tend toward jobs in cities where their skills are locally rare, thus raising their wages.

This study uses online job search queries and job postings in China to understand shifts in the labor market that took place in the wake of the COVID-19 pandemic. It found that job seekers migrated from large to small cities and from northern to southern regions. Furthermore, the supply of blue-collar jobs decreased substantially, while regional mismatch lessened.

Gun ownership and gun violence are both prevalent in the United States. Using urban scaling theory, this study finds proportionately more firearm violence in larger US cities and gun access and ownership in smaller cities. Exploring deviations from the scaling laws informs our understanding of the role of self-protection.

This study compares urban activities by frequency and matches them with socioeconomic data in three US cities. It found that mobility patterns predict economic outputs but it is the infrequent activities (for example, going to French restaurants) that have the highest explanatory power.

This study assesses the effects of working-from-home on vehicle miles traveled and transit ridership during the pandemic and finds a direct and negative relationship between them: a 1% decrease in onsite workers corresponds to a 0.99% decrease in vehicle miles traveled and a 2.26% decrease in transit ridership.

This study designs a new model based on medium-resolution satellite imagery to assess building damage from war, using the cases of Syria and Ukraine. It found that building damage has broader consequences for the population affected, especially when accounting for hospitals and schools.

This study uncovers the surprising interconnectedness of urban centers globally, finding that 3.2 billion individuals can access multiple urban tiers ranging from towns to large cities within an hour’s travel. It particularly emphasizes the strategic importance of intermediate cities in linking various urban and rural areas, crucial for effective regional development.