Academic Collaboration via Resource Contributions: An Egocentric Dataset
Data
2020Autor
Bojanowski, Michał
Czerniawska, Dominika
Fenrich, Wojciech
Metadane
Pokaż pełny rekordStreszczenie
In order to understand scientists’ incentives to form collaborative
relations, we have conducted a study looking into academically
relevant resources, which scientists contribute into collaborations
with others. The data we describe in this paper are an egocentric
dataset assembled by coding originally qualitative material. It is 40
multiplex ego networks containing data on individual attributes (such
as gender, scientific degree), collaboration ties (including alter–alter
ties), and resource flows. Resources are coded using a developed
inventory of 25 types of academically relevant resources egos and
alters contribute into their collaborations. We share the data with the
research community with the hopes of enriching knowledge and
tools for studying sociological and behavioral aspects of science as
a social process.
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