Journal of Data and Information Science  2019, Vol. 4 Issue (4): 84-95    DOI: 10.2478/jdis-2019-0022
 Research Paper
Are Contributions from Chinese Physicists Undercited?
Jinzhong Guo1,2,Xiaoling Liu1,Liying Yang2,Jinshan Wu3,()

Abstract

Purpose: In this work, we want to examine whether or not there are some scientific fields to which contributions from Chinese scholars have been under or over cited.

Design/methodology/approach: We do so by comparing the number of received citations and the IOF of publications in each scientific field from each country. The IOF is calculated from applying the modified closed system input-output analysis (MCSIOA) to the citation network. MCSIOA is a PageRank-like algorithm which means here that citations from the more influential subfields are weighted more towards the IOF.

Findings: About 40% of subfields in physics in China are undercited, meaning that their net influence ranks are higher (better) than the direct rank, while about 75% of subfields in the USA and German are undercited

Research limitations: Only APS data is analyzed in this work. The expected citation influence is assumed to be represented by the IOF, and this can be wrong.

Practical implications: MCSIOA provides a measure of net influences and according to that measure. Overall, Chinese physicists’ publications are more likely overcited rather than being undercited.

Originality/value: The issue of under or over cited has been analyzed in this work using MCSIOA.

Received: 23 September 2019      Published: 19 December 2019
Corresponding Authors: Jinshan Wu     E-mail: jinshanw@bnu.edu.cn
 Figure 1. (a) paper B, in field 75.10 (also 75.30, 75.40, and 75.50) and from Japan, is cited by paper A, in field 75.10 (also 75.30) and from the USA, German and Japan. (b) Citations (from A to B and from A to C) are converted into a citation network among the countries × subfields of physics. Figure 2. The direct citations are shown on a world map. For each node c, we show the number of received citations and the calculated IOF, $S_{IO}^{c}$. On each edge $e _{i}^{j}$ on the world map, we code with the thickness of the line the value of both $x _{i}^{j}$ and $x _{i}^{j}$:$e _{ j }^{i}$ is the line near i and $e _{ j }^{i}$ is the line near j. Each edge is also color-coded: the line starting from i is red when $x _{i}^{j}$> $x _{j}^{i}$ and green otherwise. Figure 3. The net influence rank of countries × subfields. Each country is represented by its flag. The ones with higher net influence rank than the direct rank are above the diagonal line, thus undercited, while they are under the diagonal line when their net influence ranks are lower, thus overcited. Figure 4. (a) Percentage of undercited fields of each country are plotted in a figure of the number of undercited fields v.s. the number of contributed fields. More information than just the percentage of undercited fields can be seen from (b) the relative and absolute ranking difference between the net and the direct rank of each country c. Table 1 Top 10 undercited or overcited subfields of USA and China.