Recent decades have seen a rise in the use of physics methods to study different societal
phenomena. This development has been due to physicists venturing outside of their …

The number of network science applications across many different fields has been rapidly
increasing. Surprisingly, the development of theory and domain-specific applications often …

Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …

Graphs, such as social networks, word co-occurrence networks, and communication
networks, occur naturally in various real-world applications. Analyzing them yields insight …

Egocentric network analysis is used widely across the social sciences, especially in
anthropology, political science, economics, and sociology, and is increasingly being …

Introduction The natural disasters and climate anomalies caused by increasing global
carbon emissions have seriously threatened public health. To solve increasingly serious …

Grasping the structure of the spatial associations in the energy–carbon emission efficiency
(ECEE) of the transportation industry is of great importance for ensuring the green and …

This paper provides a general overview on different perspectives and studies on social
cohesion, offers a definition of social cohesion that is deeply rooted in current literature, and …

Machine learning is a field at the intersection of statistics and computer science that uses
algorithms to extract information and knowledge from data. Its applications increasingly find …

When people are facing difficulties, they often feel the need for a confidant-a person to vent
to or a sympathetic ear with whom to talk things through. How do they decide on whom to …