Bibliometric tools for discovering information in database
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 9799, Page: 193-203
2016
- 15Citations
- 75Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
In bibliometrics, there are two main procedures to explore a research field: performance analysis and science mapping. Performance analysis aims at evaluating groups of scientific actors (countries, universities, departments, researchers) and the impact of their activity on the basis of bibliographic data. Science mapping aims at displaying the structural and dynamic aspects of scientific research, delimiting a research field, and quantifying and visualizing the detected sub-fields by means of co-word analysis or documents co-citation analysis. In this paper we present two bibliometric tools that we have developed in our research laboratory SECABA: (i) H-Classics to develop performance analysis based on Highly Cited Papers and (ii) SciMAT to develop science mapping guided by performance bibliometric indicators.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84978906816&origin=inward; http://dx.doi.org/10.1007/978-3-319-42007-3_17; http://link.springer.com/10.1007/978-3-319-42007-3_17; http://link.springer.com/content/pdf/10.1007/978-3-319-42007-3_17; https://doi.org/10.1007%2F978-3-319-42007-3_17; https://dx.doi.org/10.1007/978-3-319-42007-3_17; https://link.springer.com/chapter/10.1007/978-3-319-42007-3_17
Springer Nature
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know