Measuring Co-Authorship and Networking-Adjusted Scientific Impact
Author Information
Author(s): John P. A. Ioannidis
Primary Institution: University of Ioannina School of Medicine
Hypothesis
Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship.
Conclusion
The proposed indices may help in adjusting productivity and citation metrics to account for co-authorship behavior.
Supporting Evidence
- Co-authorship patterns can significantly influence the perceived impact of scientific work.
- Current metrics do not account for the varying contributions of co-authors in publications.
- The proposed indices aim to provide a clearer picture of a scientist's networking behavior.
Takeaway
This study looks at how many authors work together on scientific papers and suggests ways to measure their contributions better.
Methodology
The study defines new indices to measure co-authorship and networking intensity based on publication records.
Potential Biases
There is a risk of inflating networking indices due to common names and clustering of authors.
Limitations
The indices may be affected by the number of indexed papers and citations depending on the database used.
Digital Object Identifier (DOI)
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