What is he best known for?
The fields of study he is best known for:
- The Internet
- Social science
- Software
Knowledge management, Data science, World Wide Web, Open-source software development and Structure are his primary areas of study.
Kevin Crowston conducted interdisciplinary study in his works that combined Knowledge management and Citizen science.
His Data science study integrates concerns from other disciplines, such as Social network analysis, Open source software and TRACE.
His work on Web page as part of his general World Wide Web study is frequently connected to Hierarchy, Research process and Research groups, thereby bridging the divide between different branches of science.
His biological study spans a wide range of topics, including Personal software process, Software walkthrough, Software peer review, Software engineering and Social software engineering.
Kevin Crowston studied Management science and Field that intersect with Perspective.
His most cited work include:
- The interdisciplinary study of coordination (2808 citations)
- What is coordination theory and how can it help design cooperative work systems (707 citations)
- Tools for Inventing Organizations: Toward a Handbook of Organizational Processes (678 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Knowledge management, World Wide Web, Citizen science, Open source software and Data science.
As a member of one scientific family, he mostly works in the field of Knowledge management, focusing on Context and, on occasion, The Internet.
Web page is the focus of his World Wide Web research.
Citizen science is connected with Crowdsourcing, Public relations, Data quality and Task in his research.
His research in Open source software intersects with topics in Open source, Software engineering and Project success.
As part of the same scientific family, he usually focuses on Social software engineering, concentrating on Software peer review and intersecting with Personal software process.
He most often published in these fields:
- Knowledge management (33.65%)
- World Wide Web (16.99%)
- Citizen science (12.50%)
What were the highlights of his more recent work (between 2015-2021)?
- Citizen science (12.50%)
- Knowledge management (33.65%)
- Data science (10.90%)
In recent papers he was focusing on the following fields of study:
Kevin Crowston mainly focuses on Citizen science, Knowledge management, Data science, Artificial intelligence and Task.
His Knowledge management research includes elements of Control and Software.
As a part of the same scientific family, Kevin Crowston mostly works in the field of Data science, focusing on Schema and, on occasion, Action.
His studies examine the connections between Artificial intelligence and genetics, as well as such issues in Machine learning, with regards to Simple.
His Task research incorporates themes from Open-source software development, Event, Web application, Novelty and Software engineering.
His research on Crowdsourcing also deals with topics like
- Social psychology which intersects with area such as Altmetrics and Representation,
- Context and related Perspective, Fantasy, Data quality, Cheating and Variety.
Between 2015 and 2021, his most popular works were:
- Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science (118 citations)
- Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science (89 citations)
- Attitudes and norms affecting scientists' data reuse. (32 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Social science
- Software
Kevin Crowston mostly deals with Citizen science, Knowledge management, Crowdsourcing, Data science and Social psychology.
His work carried out in the field of Knowledge management brings together such families of science as Software and Empirical research.
The concepts of his Crowdsourcing study are interwoven with issues in Classifier, Artificial intelligence, Machine learning and Detector.
His research integrates issues of Project management and Big data in his study of Data science.
His Social psychology research is multidisciplinary, relying on both Fantasy, Computer-mediated communication, Data quality and Task.
In his study, which falls under the umbrella issue of Open-source software development, Open source software is strongly linked to Politeness theory.
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