ArticlePloS one2008
Measuring co-authorship and networking-adjusted scientific impact.
Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 83 citations in OpenAlex.
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- The Academic Impact Level of Ophthalmology Journals Published in Türkiye: A Comparative Scientometric Analysis.Beyoglu eye journal · 2025Article
- Path of excellence: A co-authorship network analysis of European Research Council grant winners in social sciences.Heliyon · 2024Article
- Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns.Journal of big data · 2023Article
- Low Sensitivity and Specificity of Existing Bibliometric Indices Gives Unrealistic Picture of an Author's Contribution to Science.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2021Article
- Seven decades of chemotherapy clinical trials: a pan-cancer social network analysis.Scientific reports · 2020Article
- Predicting translational progress in biomedical research.PLoS biology · 2019Article
- c-index and Subindices of the h-index: New Variants of the h-index to Account for Variations in Author Contribution.Cureus · 2018Article
- Dynamics of co-authorship and productivity across different fields of scientific research.PloS one · 2018Article
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- Ethics of using language editing services in an era of digital communication and heavily multi-authored papers.Science and engineering ethics · 2014Article
- The Scientific Competitiveness of Nations.PloS one · 2014Article
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- Citation marketing and networking.Die Naturwissenschaften · 2011Article
- Evaluating research and impact: a bibliometric analysis of research by the NIH/NIAID HIV/AIDS clinical trials networks.PloS one · 2011Article
- Co-authorship network analysis: a powerful tool for strategic planning of research, development and capacity building programs on neglected diseases.PLoS neglected tropical diseases · 2009Article
- Looking for landmarks: the role of expert review and bibliometric analysis in evaluating scientific publication outputs.PloS one · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I(1) for a single scientist as the number of authors who appear in at least I(1) papers of the specific scientist. For a group of scientists or institution, I(n) is defined as the number of authors who appear in at least I(n) papers that bear the affiliation of the group or institution. I(1) depends on the number of papers authored N(p). The power exponent R of the relationship between I(1) and N(p) categorizes scientists as solitary (R>2.5), nuclear (R = 2.25-2.5), networked (R = 2-2.25), extensively networked (R = 1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. I(n) similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.