# Field-normalized citation impact indicators and the choice of an appropriate counting method

arXiv: https://arxiv.org/abs/1501.04431 · HTML: https://mlsanity.com/paper/1501.04431/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jan 2015.

## Built on by (most cited first, 2 of 2)

- [Academic journals' AI policies fail to curb the surge in AI-assisted academic writing](https://mlsanity.com/paper/2512.06705/) (2025)
- [Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs](https://mlsanity.com/paper/2304.12217/) (2023)

## Abstract (arXiv)

Bibliometric studies often rely on field-normalized citation impact indicators in order to make comparisons between scientific fields. We discuss the connection between field normalization and the choice of a counting method for handling publications with multiple co-authors. Our focus is on the choice between full counting and fractional counting. Based on an extensive theoretical and empirical analysis, we argue that properly field-normalized results cannot be obtained when full counting is used. Fractional counting does provide results that are properly field normalized. We therefore recommend the use of fractional counting in bibliometric studies that require field normalization, especially in studies at the level of countries and research organizations. We also compare different variants of fractional counting. In general, it seems best to use either the author-level or the address-level variant of fractional counting.