ArticlePloS one2015
The Pagerank-Index: Going beyond Citation Counts in Quantifying Scientific Impact of Researchers.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Article
- Virus-host protein co-expression networks reveal temporal organization and strategies of viral infection.iScience · 2023Article
- Eigenvector PageRank difference as a measure to reveal topological characteristics of the brain connectome for neurosurgery.Journal of neuro-oncology · 2022Article
- Inequality and inequity in network-based ranking and recommendation algorithms.Scientific reports · 2022Article
- The data-index: An author-level metric that values impactful data and incentivizes data sharing.Ecology and evolution · 2021Article
- Scenes From Tick Physiology: Proteins of Sialome Talk About Their Biological Processes.Frontiers in cellular and infection microbiology · 2021Article
- Beyond eloquence and onto centrality: a new paradigm in planning supratentorial neurosurgery.Journal of neuro-oncology · 2020Article
- Scientometrics in medical journals: Indices, their pros and cons.Indian journal of anaesthesia · 2019Article
- Evaluating the impact of citations of articles based on knowledge flow patterns hidden in the citations.PloS one · 2019Article
- On the networked architecture of genotype spaces and its critical effects on molecular evolution.Open biology · 2018Review
- Researcher and Author Impact Metrics: Variety, Value, and Context.Journal of Korean medical science · 2018Review
- H-index in medicine is driven by original research.Croatian medical journal · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying and comparing the scientific output of researchers has become critical for governments, funding agencies and universities. Comparison by reputation and direct assessment of contributions to the field is no longer possible, as the number of scientists increases and traditional definitions about scientific fields become blurred. The h-index is often used for comparing scientists, but has several well-documented shortcomings. In this paper, we introduce a new index for measuring and comparing the publication records of scientists: the pagerank-index (symbolised as π). The index uses a version of pagerank algorithm and the citation networks of papers in its computation, and is fundamentally different from the existing variants of h-index because it considers not only the number of citations but also the actual impact of each citation. We adapt two approaches to demonstrate the utility of the new index. Firstly, we use a simulation model of a community of authors, whereby we create various 'groups' of authors which are different from each other in inherent publication habits, to show that the pagerank-index is fairer than the existing indices in three distinct scenarios: (i) when authors try to 'massage' their index by publishing papers in low-quality outlets primarily to self-cite other papers (ii) when authors collaborate in large groups in order to obtain more authorships (iii) when authors spend most of their time in producing genuine but low quality publications that would massage their index. Secondly, we undertake two real world case studies: (i) the evolving author community of quantum game theory, as defined by Google Scholar (ii) a snapshot of the high energy physics (HEP) theory research community in arXiv. In both case studies, we find that the list of top authors vary very significantly when h-index and pagerank-index are used for comparison. We show that in both cases, authors who have collaborated in large groups and/or published less impactful papers tend to be comparatively favoured by the h-index, whereas the pagerank-index highlights authors who have made a relatively small number of definitive contributions, or written papers which served to highlight the link between diverse disciplines, or typically worked in smaller groups. Thus, we argue that the pagerank-index is an inherently fairer and more nuanced metric to quantify the publication records of scientists compared to existing measures.
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.