The observed architecture of ecological and socio-economic networks differssignificantly from that of random networks. From a network science standpoint, non-random structural …
How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is …
Humans recognize the visual world at multiple levels: we effortlessly categorize scenes and detect objects inside, while also identifying the textures and surfaces of the objects along …
This book is principally intended for social scientists wanting to undertake social network research. It assumes the reader already knows a thing or two (perhaps even a lot) about …
TAB Snijders - Annual review of statistics and its application, 2017 - annualreviews.org
This article discusses the stochastic actor-oriented model for analyzing panel data of networks. The model is defined as a continuous-time Markov chain, observed at two or more …
Anomalies in online social networks can signify irregular, and often illegal behaviour. Detection of such anomalies has been used to identify malicious individuals, including …
The application of method and theory from network science to archaeology has dramatically increased over the last decade. In this article, we document this growth over time, discuss …
The rise of big data—data that are not only large and massively multivariate but concern a dizzying array of phenomena—represents a watershed moment for the social sciences …
Over the last fifty years, research into street networks has gained prominence with a rapidly growing number of studies across disparate disciplines. These studies investigate a wide …