Specialization and Impact Analysis Combined
Combining the specialization index and HCA reveals scientific fields where countries are above the world average for both volume (specialization index) and impact (HCA). The positional analysis uses a bubble chart where countries to the right of the vertical axis produce a greater than average number of publications in the field. Countries above the horizontal axis have a higher HCA and therefore have more impact in the scientific field. The size of the bubble corresponds to the volume of output. Therefore, countries in the upper right quadrant of the graph are above the world average in both production and impact.
Using bubble charts, the fields of health sciences and computer and information sciences display markedly different clustering among the 15 largest-producing countries. The western countries show greater scientific impact and concentration in the health sciences (Figure 5a-10), while China shows greater impact and concentration in computer and information sciences (Figure 5a-11). In health sciences, the United States is 34% more specialized than the world average and nearly twice as impactful compared to the world average (Figure 5a-10). In computer and information sciences, articles produced by authors from U.S. institutions are more than twice as likely to be in the top 1% most-cited articles (2.2), but concentration in the field (0.7) is less than the world average (Figure 5a-11). Meanwhile articles produced by authors from Chinese institutions are above the world average for highly cited papers (1.7) and above the world average level of concentration (1.1) (Figure 5a-11).
S&E articles-based positional analysis in health sciences for the 15 largest producing countries: 2016
Note(s):
Articles are classified by their year of publication and are assigned to a region, country, or economy on the basis of the institutional address(es) of the author(s) listed in the article. The specialization index (SI) is calculated as follows: SI = (Fe/Te)/(Fw/Tw) where Fe is the fractional paper count of a given region, country, or economy's output in a given field (F), Te is the total (T) output for the entity, Fw is the total ouput of the world in the same field, and Tw is the total output across all fields at the world level. The 15 largest publication-producing countries of S&E in 2018 were selected (see Table 5a-1). Countries are colored according to their main region (see Table S5a-1 for a definition of the regions). The axes are log-normalized to facilitate the display of the data. Citation data are based on all citations made to articles in their publication year and all following years and are normalized by subfield and publication year to allow for comparisons across subfields and over time, resulting in the world-level standing at 1.0 for each subfield and year. A minimum 2-year citation window is needed for a relative citation (RC) score to be computed. This results in scores regarding highly cited articles not being computed after 2016 because the citation window for more recent years is not yet complete. The share of articles in the top 1% is computed as follows: Sx = HCAx/Ax, where Sx is the share of output from country x in the top 1% most-cited articles; HCAx is the number of articles from country x that are among the top 1% of most-cited articles (using full counting, with the exception of papers at the limit of the top 1%, which are fractioned so the world average can stand at 1%); and Ax is the total number of articles from country x with an RC score, which excludes articles released after 2016 and unclassified publications. The raw data (not transformed) are available in Table S5a-10, Table S5a-25, and Table S5a-43.
Source(s):
National Center for Science and Engineering Statistics, National Science Foundation; Science-Metrix; Elsevier, Scopus abstract and citation database, accessed June 2019.
Science and Engineering Indicators
S&E articles-based positional analysis in computer and information sciences for the 15 largest producing countries: 2016
Note(s):
Articles are classified by their year of publication and are assigned to a region, country, or economy on the basis of the institutional address(es) of the author(s) listed in the article. The specialization index (SI) is calculated as follows: SI = (Fe/Te)/(Fw/Tw) where Fe is the fractional paper count of a given region, country, or economy's output in a given field (F), Te is the total (T) output for the entity, Fw is the total ouput of the world in the same field, and Tw is the total output across all fields at the world level. The 15 largest publication-publishing countries of S&E in 2018 were selected (see Table 5a-1). Countries are colored according to their main region (see Table S5a-1 for a definition of the regions). The axes are log-normalized to facilitate the display of the data. Citation data are based on all citations made to articles in their publication year and all following years and are normalized by subfield and publication year to allow for comparisons across subfields and over time, resulting in the world-level standing at 1.0 for each subfield and year. A minimum 2-year citation window is needed for a relative citation (RC) score to be computed. This results in scores regarding highly cited articles not being computed after 2016 because the citation window for more recent years is not yet complete. The share of articles in the top 1% is computed as follows: Sx = HCAx/Ax, where Sx is the share of output from country x in the top 1% most-cited articles; HCAx is the number of articles from country x that are among the top 1% of most-cited articles (using full counting, with the exception of papers at the limit of the top 1%, which are fractioned so the world average can stand at 1%); and Ax is the total number of articles from country x with an RC score, which excludes articles released after 2016 and unclassified publications. The raw data (not transformed) are available in Table S5a-7, Table S5a-22, and Table S5a-40.
Source(s):
National Center for Science and Engineering Statistics, National Science Foundation; Science-Metrix; Elsevier, Scopus abstract and citation database, accessed June 2019.
Science and Engineering Indicators
More broadly, the western economies demonstrate more specialization and impact in astronomy and astrophysics, biological and biomedical sciences, geosciences, health sciences, psychology, and social sciences (Table S5a-19, Table S5a-20, Table S5a-24, Table S5a-25, Table S5a-30, Table S5a-31, Table S5a-37, Table S5a-38, Table S5a-42, Table S5a-43, Table S5a-48, and Table S5a-49). Eastern economies demonstrate more specialization and impact in chemistry, computer and information sciences, engineering, and material sciences (Table S5a-21, Table S5a-22, Table S5a-23, Table S5a-26, Table S5a-39, Table S5a-40, Table S5a-41, and Table S5a-44).