h2-tail index
The h-index describes an h×h square under the citation curve containing h2 citations. Bornmann et al. (2010) suggest dividing the citation curve into three sections based on this square and describing each section as the percent of all citations found within the section.
The h2-tail index is the percent of citations found within the tail of the citation curve, i.e., the citations of publications outside the h-core. It is calculated as:$$h_\text{tail}^2=\frac{C^P - C^H}{C^P}\times 100=\frac{\sum\limits_{i=h+1}^{P}{C_i}}{C^P}\times 100$$History
| Year | \(h_\text{tail}^2\) |
|---|---|
| 1997 | 50.0000 |
| 1998 | 35.7143 |
| 1999 | 15.9091 |
| 2000 | 7.6923 |
| 2001 | 9.2199 |
| 2002 | 13.7795 |
| 2003 | 11.5869 |
| 2004 | 12.5984 |
| 2005 | 9.6567 |
| 2006 | 8.8608 |
| 2007 | 8.1564 |
| 2008 | 6.9809 |
| 2009 | 4.3684 |
| 2010 | 5.5007 |
| 2011 | 4.8383 |
| 2012 | 3.4345 |
| 2013 | 3.2492 |
| 2014 | 2.9407 |
| 2015 | 3.0949 |
| 2016 | 3.3742 |
| 2017 | 2.8616 |
| 2018 | 3.3026 |
| 2019 | 3.6362 |
| 2020 | 3.8640 |
| 2021 | 3.7734 |
| 2022 | 3.6495 |
| 2023 | 3.6032 |
| 2024 | 3.6470 |
References
- Bornmann, L., R. Mutz, and H.-D. Daniel (2010) The h index research output measurement: Two approaches to enhance its accuracy. Journal of Informetrics 4:407–414.