Ethnography beyond thick data

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

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.

• Jezik: Angleški jezik
• Ključne besede: anthropological research, machine learning, big data, data analysis, circular mixed methods, computational anthropology, computer-based methods, thick data
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FRI - Fakulteta za računalništvo in informatiko; FF - Filozofska fakulteta
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2024
• Št. strani: Str. 272–88
• Številčenje: Vol. 48, iss. 2
• PID: 20.500.12556/RUL-165193
• UDK: 004.6:39
• ISSN pri članku: 2153-957X
• DOI: 10.1111/napa.12226
• COBISS.SI-ID: 207933443
• Datum objave v RUL: 26.11.2024

Gradivo je del revije

• Naslov: Annals of anthropological practice
• Skrajšan naslov: Ann. anthropol. pract.
• Založnik: Wiley, American Anthropological Association
• ISSN: 2153-957X
• COBISS.SI-ID: 518174233

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: antropološke raziskave, strojno učenje, masovni podatki, analiza podatkov