Using Digital Trace Analytics to Understand and Enhance Scientific Collaboration View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Laura C. Anderson , Cheryl A. Kieliszewski

ABSTRACT

Social interaction and idea flow have been shown to be important factors in the collaboration work of scientific and technical teams. This paper describes a study to investigate scientific team collaboration and activity through digital trace data. Using a 27-month electronic mail data corpus from a scientific research project, we analyze team member participation and topics of discussion as a proxy for interaction and idea flow. Our results illustrate the progression of participation and conversational themes over the project lifecycle. We identify temporal evolution of work activities, influential roles and formation of communities throughout the project, and conversational aspects in the project lifecycle. This work is the first step of a larger research program analyzing multiple sources of digital trace data to understand team activity through organic products and byproducts of work. More... »

PAGES

195-205

References to SciGraph publications

  • 2014. Understanding User Behavior Through Log Data and Analysis in WAYS OF KNOWING IN HCI
  • 2014-10. Email mining: tasks, common techniques, and tools in KNOWLEDGE AND INFORMATION SYSTEMS
  • Book

    TITLE

    Advances in Artificial Intelligence, Software and Systems Engineering

    ISBN

    978-3-319-94228-5
    978-3-319-94229-2

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-94229-2_19

    DOI

    http://dx.doi.org/10.1007/978-3-319-94229-2_19

    DIMENSIONS

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