murari023 / SciImpactRanking

Use rank percentile in evaluating and predicting scientific impact

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On the Usage of Rank Percentile in Evaluating and Predicting Scientific Impacts

This project studies utilizing rank percentile to evaluate publication or scholar impact. The percentile indicator is demonstrated to be highly predictive, and hence it can be utilized in combination with other metrics to picture the trajectory of a scholar or a publication and assist in academic decision making. For more details, see our paper Tian, S. and Ipeirotis, P. (2021): "On the Usage of Rank Percentile in Evaluating and Predicting Scientific Impacts".

This repository provides the dataset and the code to reproduce the results in the paper.

If cloning the repository is not an option, the raw dataset from Google Scholar can be downlowed from here, and the rank percentiles generated by the **code/calcRP.R' script can be downloaded from here.

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Use rank percentile in evaluating and predicting scientific impact


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