The pairing of massive data sets with processes—or algorithms—written in computer code to
sort through, organize, extract, or mine them has made inroads in almost every major social …

Computational social science is more than just large repositories of digital data and the
computational methods needed to construct and analyse them. It also represents a …

Machine-learning (ML) methods have gained prominence in the quantitative sciences.
However, there are many known methodological pitfalls, including data leakage, in ML …

It has become trivial to point out that algorithmic systems increasingly pervade the social
sphere. Improved efficiency—the hallmark of these systems—drives their mass integration …

Background Chronic and/or extreme stress in early life, often referred to as early adversity,
childhood trauma, or early life stress, has been associated with a wide range of adverse …

We explore the impact of COVID-19 on employee's digital communication patterns through
an event study of lockdowns in 16 large metropolitan areas in North America, Europe and …

In light of fast‐growing popular, political and professional discourses around AI in education,
this article outlines five broad areas of contention that merit closer attention in future …

NEW YORK TIMES BESTSELLER From the Nobel Prize-winning author of Thinking, Fast
and Slow and the coauthor of Nudge, a revolutionary exploration of why people make bad …

We argue that it is useful to distinguish between three key goals of personality science—
description, prediction and explanation—and that attaining them often requires different …

The interdisciplinary field of knowledge discovery and data mining emerged from a
necessity of big data requiring new analytical methods beyond the traditional statistical …