Get thicker data naturally with computational anthropology

Description

A chameleon among the humanities and social sciences, anthropology explores the human experience through a patchwork of methods and modes of expression beyond the hypothesis, including written stories, documentary film, and computational analysis. Anthropologists have a long history of combining qualitative methods (e.g., ethnography) with computational methods for things like social network analysis, generating kinship diagrams, and even parsing folklore narratives. Software engineering and data science are fundamentally about human behavior problems, yet software engineers and data scientists are poorly equipped for the ambiguity and social impacts of these “human behavior solutions” we release into the world.

Augustina Ragwitz covers fundamental concepts in anthropology to explore what computational anthropology might look like, what happens when we qualify the quantities and thicken the big data, and what tech industry professionals and researchers could learn from an anthropological approach to computational analysis. She highlights open source examples of computational research analysis used in anthropological research on GitHub. You’ll also get resources for professional training in ethnography and connecting with applied anthropologists working in the industry to help your career growth.