Name
Abstract | ||
|---|---|---|
The term “non-citation factor” refers to the percentage of never-cited papers in a citation time window, a common phenomenon in the science world. Some scholars have qualitatively explored the reasons for not citing a publication, and quantitatively analyzed the mathematical functional relations between the “non-citation factor” and “impact factor of a journal.” This study simultaneously considers the mutual relations and closeness degree between the “non-citation factor” and different influencing factors from a novel perspective—that of using a more structuralized panel data model. The analysis revealed that the determinants, including “impact factor of journal,” “age of journal,” “average number of references per paper in journal,” and “issues of journal,” exerted an extremely small but positive influence (< 0.025) on the decline of “percentage of never-cited papers in the citation time window of publication year or 3 years.” That means the improvement of these determinants can decrease the percentage of never-cited papers. The “impact factor of the journal” always had the biggest positive influence, while the “average number of references per paper in journal” always had the smallest positive influence. In wider citation time windows of 3 or 6 years, two determinants—“number of publications in journal” and “amount of interdisciplinarity in journal”—began to exert a negative effect with a positive correlation coefficient on the decline of the “non-citation factor.” That means the improvement of these two determinants cannot decrease the value of the “non-citation factor,” even though they can increase its value. It is worth noting that the “impact factor of the journal” had a positive influence on the decline of the percentages of never-cited papers in the citation time window of publication year or 3 years, and began to play a negative role in the decline of percentage of never-cited papers in the citation time window of 6 years. Finally, three variables—“average number of authors per paper in journal,” “average number of references per paper in journal,” and “issues of journal”—no longer exerted an influence on the decline of percentages of never-cited papers in the citation time window of 6 years, while “age of journal” and “average number of pages per paper in journal” still made a positive contribution. Our findings could help research institutions, researchers, editors, and publishers understand the positively or negatively influential factors that lead to non-citation, thus improving the chance of papers being cited and having some academic influence. |
Year | DOI | Venue |
|---|---|---|
2018 | https://doi.org/10.1007/s11192-018-2791-x | Scientometrics |
Keywords | Field | DocType |
Non-citation,Uncitedness,Determinant,Impact factor,Panel data model,Quantitative analysis,Bibliometric analysis,Interdisciplinary,Author and references | Econometrics,Panel data,Data mining,Computer science,Closeness,Citation,Positive correlation,Impact factor | Journal |
Volume | Issue | ISSN |
116 | 2 | 0138-9130 |
Citations | PageRank | References |
1 | 0.35 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zewen Hu | 1 | 14 | 2.00 |
| Yishan Wu | 2 | 105 | 10.78 |
| Jianjun Sun | 3 | 19 | 3.07 |