TY - JOUR
T1 - Participative epistemology in social data science
T2 - Combining ethnography with computational and statistical approaches
AU - Campagnolo, Gian Marco
N1 - Funding Information:
The project has been funded by the University of Edinburgh Challenge Investment Fund for risk taking and experimentation with new disciplinary fields. It also received support from the Alan Turing Institute Faculty Fellowship and Visiting Research schemes.
Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022/5/4
Y1 - 2022/5/4
N2 - In this paper, I introduce the notion of participative epistemology and discuss how it can contribute to make social data science more accountable. I do so by offering the case of a project where ethnographic, computational and sequence analysis methods have been used in combination. By presenting here in greater detail research design and pilot results of a project using professional networking data to understand the careers of IT industry analysts, I suggest a view on the collaboration between data science and social science as coordinated labour. The application of participative epistemology to social data science is articulated in three points: (1) a more tactical view on the partnerships with commercial data where shared value system is not a pre-requisite for coordinated knowledge production; (2) an appreciation for complementarities in perspective between phenomenological sociology, expertise in computer science associated to digitalisation and the narrative positivism linked with the use of statistics and (3) a view on social data science as contributing empirical sociology with new sensitizing concepts, taking ethnography to reflectively address its own presuppositions.
AB - In this paper, I introduce the notion of participative epistemology and discuss how it can contribute to make social data science more accountable. I do so by offering the case of a project where ethnographic, computational and sequence analysis methods have been used in combination. By presenting here in greater detail research design and pilot results of a project using professional networking data to understand the careers of IT industry analysts, I suggest a view on the collaboration between data science and social science as coordinated labour. The application of participative epistemology to social data science is articulated in three points: (1) a more tactical view on the partnerships with commercial data where shared value system is not a pre-requisite for coordinated knowledge production; (2) an appreciation for complementarities in perspective between phenomenological sociology, expertise in computer science associated to digitalisation and the narrative positivism linked with the use of statistics and (3) a view on social data science as contributing empirical sociology with new sensitizing concepts, taking ethnography to reflectively address its own presuppositions.
KW - social data science
KW - ethnography
KW - interdisciplinarity
KW - sociology of professions
U2 - 10.1080/13645579.2021.1892379
DO - 10.1080/13645579.2021.1892379
M3 - Article
SN - 1364-5579
VL - 25
SP - 391
EP - 403
JO - International Journal of Social Research Methodology
JF - International Journal of Social Research Methodology
IS - 3
ER -