Alina Arseniev-Koehler

Alina Arseniev-Koehler is a computational and cultural sociologist with substantive interests in language, health, and social categories. Alina strives to clarify core concepts and debates about cultural meaning in sociology. For example, how do individuals learn and deploy stereotypes? Empirically, Alina focuses on cases where meaning is linked to inequality and health, such as the moral meanings attached to body weight, the stigmatizing meanings of disease, and gender stereotypes. To investigate these topics, Alina uses computational methods and machine learning, especially computational text analysis.

Alina’s work also circles around a methodological question: how can scientists measure meanings encoded in text data, such as news articles and social media posts? Computational text analysis requires scientists to mathematically model the nuanced ways in which human language encodes and conveys meaning. As highlighted by Alina’s work, innovation in computational text analysis is tightly intertwined with innovation in theoretical understanding of meanings.

Alina received a B.A. in Sociology from University of Washington in 2014, and a master’s and Ph.D. in Sociology from the University of California, Los Angeles in 2022.

Specializations: Culture; cognition; language; health; stigma; computational social science; text analysis