The science of science (SOS) is a rapidly developing field which aims to understand,
quantify and predict scientific research and the resulting outcomes. The problem is …

Networks are finite metric spaces, with distances defined by the shortest paths between
nodes. However, this is not the only form of network geometry: two others are the geometry …

There has been a surge of recent interest in graph representation learning (GRL). GRL
methods have generally fallen into three main categories, based on the availability of …

Learning from graph-structured data is an important task in machine learning and artificial
intelligence, for which Graph Neural Networks (GNNs) have shown great promise. Motivated …

We argue word embedding models are a useful tool for the study of culture using a historical
analysis of shared understandings of social class as an empirical case. Word embeddings …

Complex systems must respond to external perturbations and, at the same time, internally
distribute information to coordinate their components. Although networked backbones help …

The Matthew effect describes the phenomenon that in societies, the rich tend to get richer
and the potent even more powerful. It is closely related to the concept of preferential …

This article introduces the Causal Attitude Network (CAN) model, which conceptualizes
attitudes as networks consisting of evaluative reactions and interactions between these …

Network analysis is a powerful tool that provides us a fruitful framework to describe
phenomena related to social, technological, and many other real-world complex systems. In …

Rapid research progress in science and technology (S&T) and continuously shifting
workforce needs exert pressure on each other and on the educational and training systems …