Ethnography beyond thick data

Pretnar Žagar, Ajda (author), Podjed, Dan (author)

This article presents opportunities for enriching anthropological knowledge and methods with machine learning and data analysis. Different examples show how quantitative methods empower anthropologists and how computational methods supplement ethnography, from sensor data and interview transcripts to designing technology solutions and automatically labeling cultural heritage. Conversely, the authors discuss the benefits of qualitative approaches in contemporary anthropological research and show how to transition from data analysis to ethnography and vice versa. Finally, the article pinpoints aspects in which each method can fail individually. It discusses why a combination of the two approaches, called circular mixed methods, minimizes the chance of failure and maximizes insights from the data.

• Language: English
• Keywords: anthropological research, machine learning, big data, data analysis, circular mixed methods, computational anthropology, computer-based methods, thick data
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science ; FF - Faculty of Arts
• Publication status: Published
• Publication version: Version of Record
• Year: 2024
• Number of pages: Str. 272–88
• Numbering: Vol. 48, iss. 2
• PID: 20.500.12556/RUL-165193
• UDC: 004.6:39
• ISSN on article: 2153-957X
• DOI: 10.1111/napa.12226
• COBISS.SI-ID: 207933443
• Publication date in RUL: 26.11.2024

Record is a part of a journal

• Title: Annals of anthropological practice
• Shortened title: Ann. anthropol. pract.
• Publisher: Wiley, American Anthropological Association
• ISSN: 2153-957X
• COBISS.SI-ID: 518174233

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: antropološke raziskave, strojno učenje, masovni podatki, analiza podatkov