Economic inequality isn’t just limited to neighborhoods. The restaurants, stores, and other places we visit in cities are all unequal in their own way.
The Atlas of Inequality shows the income inequality of people who visit different places in the Boston metro area. It uses aggregated anonymous location data from digital devices to estimate people’s incomes and where they spend their time.
Using that data, we’ve made our own place inequality metric to capture how unequal the incomes of visitors to each place are. Economic inequality isn’t just limited to neighborhoods, it’s part of the places you visit every day.

Source: inequality.media.mit.edu

Religion is considered as a notable origin of interpersonal relations, as well as an effective and efficient tool to organize a huge number of people towards some challenging targets. At the same time, a believer prefers to make friend with other people of the same faith, and thus people of different faiths tend to form relatively isolated communities. The segregation between different religions is a major factor for many social conflicts. However, quantitative understanding of religious segregation is rare. Here we analyze a directed social network extracted from weibo.com (the largest directed social network in China, similar to twitter.com), which is consisted of 6875 believers in Christianity, Buddhism, Islam and Taoism. This religion network is highly segregative. Comparative analysis shows that the extent of segregation for different religions is much higher than that for different races and slightly higher than that for different political parties. Furthermore, we study the few cross-religion links and find 46.7% of them are probably related to charitable issues. Our findings provide quantitative insights into religious segregation and valuable evidence for religious syncretism.

 

Segregation in religion networks
Jiantao Hu, Qian-Ming Zhang and Tao Zhou
EPJ Data Science 2019 8:6
https://doi.org/10.1140/epjds/s13688-019-0184-x

Source: epjdatascience.springeropen.com

This article explores the effect of ideological polarization on team performance. By analysing millions of edits to Wikipedia, the authors reveal that politically diverse editor teams produce higher-quality articles than homogeneous or moderate teams, and they identify the mechanisms responsible for producing these superior articles.

 

The wisdom of polarized crowds
Feng Shi, Misha Teplitskiy, Eamon Duede & James A. Evans
Nature Human Behaviour (2019)

Source: www.nature.com

A theoretical model is presented for early evolutionary cell sorting within cellular aggregates. The model involves an energy-saving mechanism and principles of collective self-organization analogous to those observed in bicycle pelotons (groups of cyclists). The theoretical framework is applied to slime-mold slugs (Dictyostelium discoideum) and incorporated into a computer simulation which demonstrates principally the sorting of cells between the anterior and posterior slug regions. The simulation relies on an existing simulation of bicycle peloton dynamics which is modified to incorporate a limited range of cell metabolic capacities among heterogeneous cells, along with a tunable energy-expenditure parameter, referred to as an “output-level” or “starvation-level” to reflect diminishing energetic supply. Proto-cellular dynamics are modeled for three output phases: “active”, “suffering”, and “dying or dead.” Adjusting the starvation parameter causes cell differentiation and sorting into sub-groups within the cellular aggregate. Tuning of the starvation parameter demonstrates how weak or expired cells shuffle backward within the cellular aggregate.

 

Cell pelotons: A model of early evolutionary cell sorting, with application to slime mold Dictyostelium discoideum

HughTrenchard

Journal of Theoretical Biology
Volume 469, 21 May 2019, Pages 75-95

Source: www.sciencedirect.com

Radically new dynamics in the early 20th century transformed cars and, in turn, the world. Here’s why the next great inflection point is upon us, auguring changes no less profound.

Source: www.mckinsey.com