The emergence of big data and computational tools has introduced new possibilities for
using large-scale textual sources in sociological research. Recent work in sociology of …

This article considers the interdisciplinary opportunities and challenges of working with
digital cultural heritage, such as digitized historical newspapers, and proposes an integrated …

Unsupervised learning algorithms are widely used for many important statistical tasks with
numerous applications in science and industry. Yet despite their prevalence, they have …

With an increased focus on social well‐being in response to a burgeoning global economy
exposing the weaknesses of social welfare policies, research output in the field has grown …

Sociologists are discussing the need for more formal ways to extract meaning from digital
text archives. We focus attention on the seeded topic model, a semi-supervised extension to …

Artificial intelligence (AI) is increasingly being viewed as a creative partner rather than as a
tool. How to design such collaborations is still a subject of speculation. In this pictorial, we …

This paper addresses methodological issues in diachronic data analysis for historical
research. We apply two families of topic models (LDA and DTM) on a relatively large set of …

Today's videogames are often intertwined with profound religious narratives, content,
characters, and artifacts-but how do player communities understand the role of religion in …

Topic modeling—a text‐mining technique often used to uncover thematic structures in large
collections of texts—has been increasingly frequently used in the context of the analysis of …

A new wave of research about society has emerged, which uses computers as research
instruments. This research not only uses computers for text processing or web browsing but …