Bornakke2018

From emcawiki
Jump to: navigation, search
Bornakke2018
BibType ARTICLE
Key Bornakke2018
Author(s) Tobias Bornakke, Brian L. Due
Title Big–Thick Blending: A method for mixing analytical insights from big and thick data sources
Editor(s)
Tag(s) EMCA, big data, blending, ethnomethodology, ethnography, granularity, multimethodology, thick data
Publisher
Year 2018
Language English
City
Month
Journal Big Data & Society
Volume 5
Number 1
Pages 1-16
URL Link
DOI 10.1177%2F2053951718765026
ISBN
Organization
Institution
School
Type
Edition
Series
Howpublished
Book title
Chapter

Download BibTex

Abstract

Recent works have suggested an analytical complementarity in mixing big and thick data sources. These works have, however, remained as programmatic suggestions, leaving us with limited methodological inputs on how to archive such complementary integration. This article responds to this limitation by proposing a method for ‘blending’ big and thick analytical insights. The paper first develops a methodological framework based on the cognitivist linguistics terminology of ‘blending’. Two cases are then explored in which blended spaces are crafted from engaging big and thick analytical insights with each other. Through these examples, we learn how blending processes should be conducted as a rapid, iterative and collaborative effort with respect for individual expertise. Further, we demonstrate how the unique, but often overlooked, granularity of big data plays a key role in affording the blending with thick data. We conclude by suggesting four commonly appearing blending strategies that can be applied when relying upon big and thick data sources.

Notes