Archived
This content is available here strictly for research, reference, and/or recordkeeping and as such it may not be fully accessible. If you work or study at University of Kentucky and would like to request an accessible version, please use the SensusAccess Document Converter.
Abstract
Two mode social network data consisting of actors attending events is a common type of social network data. For these kinds of data it is also common to have additional information about the timing or sequence of the events. We call data of this type two-mode temporal data. We explore the idea that actors attending events gain information from the event in two ways. Firstly the event itself may provide information or training; secondly, as co-attendees interact, they may pass on skills or information they have gleaned from other events. We propose a method of measuring these gains and demonstrate its usefulness using the classic Southern Women Data and a covert network dataset.
Document Type
Article
Publication Date
10-2018
Digital Object Identifier (DOI)
https://doi.org/10.1016/j.socnet.2018.05.003
Funding Information
This research was supported by Leverhulme Trust Research Project Grant number R116318, PI Martin Everett.
Repository Citation
Everett, Martin G.; Broccatelli, Chiara; Borgatti, Stephen P.; and Koskinen, Johan, "Measuring Knowledge and Experience in Two Mode Temporal Networks" (2018). Management Faculty Publications. 6.
https://uknowledge.uky.edu/management_facpub/6
Notes/Citation Information
Published in Social Networks, v. 55.
© 2018 Elsevier B.V.
The copyright holder has granted the permission for posting this article here.
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
The document available for download is the authors' post-peer-review final draft of the article.