Big Data and Anthropology: Concerns for data collection in a new research context
Justin E. Lane

@article{,
title= {Big Data and Anthropology: Concerns for data collection in a new research context},
journal= {},
author= {Justin E. Lane},
year= {},
url= {},
abstract= {Traditionally, anthropologists have worked within relatively small groups of individuals; at least relative to the scope of modern big-data analytics. Traditionally, we have known our informants and participants and likely have had some personal relationship or connection with them at some level. Such research has carried with it a tradition of protection whereby anthropologists are keenly aware that we are often working in fragile parts of human societies and asking personal questions; therefore we have strived to protect the identities of our informants. However, the modern digital environment is one whereby we have access to individual’s data, sometimes deeply personal data, at the touch of a button. Given this massive amount of unique individual data, one can reverse-engineer the data in order to obtain the specific identity of the person, even if their name is changed or erased from that data. In addition, it is often the case that, when a researcher obtains social network data—even when assuming complete consent and legal transfer of the information—information concerning real individuals who have not consented to participate in the research is also transmitted. Generally, this paper argues that we have not given enough thought to such problems as online data becomes of increasing interest by anthropology. The presentation concludes that anthropologists must keep in mind a combination of “traditional” research values as well as the fact that we are in a new frontier of information as we enter the world of “big-data”. It finishes with some suggestions for participant protection.

Torrent of academic paper https://anthro.web.ox.ac.uk/sites/default/files/anthro/documents/media/jaso8_1_2016_74_88.pdf},
keywords= {big data, anthropology, culture, data mining, data science, religion, data protection, ethics, field research},
terms= {},
license= {},
superseded= {}
}