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Anthropology with algorithms?

Lisa Jenny Krieg, Moritz Berning, Anita Hardon

Medicine Anthropology Theory September 28, 2017 DOI: 10.17157/mat.4.3.458 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Case study Case report Peer reviewed
Sample size 20,000
Population Reports on drug experiences from the online drug education portal Erowid
Keywords Ethnography Field mathematics Meaning existential Big data Context archaeology Data science Epistemology World wide web Anthropology
Citations 26
Key findings Integrating ethnographic methods with computational analysis of natively digital data is highly rewarding and requires deep ethnographic knowledge, termed 'field groundedness', to make sense of visualizations.

Abstract

Based on a study of more than twenty thousand reports on drug experiences from the online drug education portal Erowid, this article argues that the integration of ethnographic methods with computational methods and digital data analysis, including so-called big data, is not only possible but highly rewarding. The analysis of ‘natively’ digital data from sites like Facebook, message boards, and web archives can offer glimpses into worlds of practice and meaning, introduce anthropologists to user-based semantics, provide greater context, help to re-evaluate hypotheses, facilitate access to difficult fields, and point to new research questions. This case study generated important insights into the social and political entanglements of drug consumption, drug phenomenology, and harm reduction. We argue here that deep ethnographic knowledge, what we term ‘field groundedness’, is indispensable for thoroughly making sense of the resulting visualizations, and we advocate for seeing ethnography and digital data analysis in a symbiotic relationship.

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