| Literature DB >> 35139134 |
Abstract
Social media has surrounded every area of life, and social media platforms have become indispensable for today's communication. Many journals use social media actively to promote and disseminate new articles. Its use to share the articles contributes many benefits, such as reaching more people and spreading information faster. However, there is no consensus in the studies that to evaluate between tweeted and non-tweeted papers regarding their citation numbers. Therefore, it was aimed to show the effect of social media on the citations of articles in the top ten communication-based journals. For this purpose, this work evaluated original articles published in the top 10 communication journals in 2018. The top 10 communication-based journals were chosen based on SCImago Journal & Country Rank (cited in 2019). Afterward, it was recorded the traditional citation numbers (Google Scholar and Thompson-Reuters Web of Science) and social media exposure of the articles in January 2021 (nearly three years after the articles' publication date). It was assumed that this period would allow the impact of the published articles (the citations and Twitter mentions) to be fully observed. Based on this assessment, a positive correlation between exposure to social media and article citations was observed in this study.Entities:
Mesh:
Year: 2022 PMID: 35139134 PMCID: PMC8827420 DOI: 10.1371/journal.pone.0263725
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
The characteristics of journals.
| Journals’ Name | 5-Years IF | IF (2019) | Q index | Issues (per year) |
|---|---|---|---|---|
|
| 5.068 | 4.339 | Q1 | 6 |
|
| N/A | 6.302 | Q1 | 5 |
|
| 7.175 | 4.846 | Q1 | 6 |
|
| N/A | 4.577 | Q1 | 2 |
|
| 4.901 | 4.286 | Q1 | 6 |
|
| N/A | 5.281 | Q1 | 4 |
|
| 4.972 | 4.577 | Q1 | 12 |
|
| 4.039 | 3.540 | Q1 | 4 |
|
| 3.259 | 2.494 | Q1 | 5 |
|
| N/A | 4.476 | Q1 | 10 |
IF: impact factor; Q index: quartile index; N/A: not available
The number of citations, mentions of Twitter and other platforms on the articles journal basis.
| Journals’ name | Articles (n) (%) | Citations (GS) | Citations (WoS) | Mentions (Twitter) | Mentions (Other platforms) |
|---|---|---|---|---|---|
|
| 29 (5.1) | 17 (3–171) | 2 (0–36) | 35 (10–417) | 42 (14–342) |
|
| 24 (4.2) | 16 (2–203) | 1 (0–10) | 0 (0–12) | 3.5 (0–878) |
|
| 57 (10) | 15 (2–191) | 5 (0–90) | 12 (0–301) | 39 (0–318) |
|
| 39 (6.8) | 16 (1–155) | 5 (0–42) | 33 (10–212) | 53 (14–396) |
|
| 39 (6.8) | 21 (2–710) | 5 (1–235) | 2 (0–164) | 42 (0–456) |
|
| 15 (2.6) | 22 (5–156) | 2 (0–13) | 3 (0–41) | 29 (6–303) |
|
| 245 (42.9) | 23 (0–468) | 7 (0–168) | 8 (0–502) | 51 (0–702) |
|
| 20 (3.5) | 9.5 (2–38) | 3.5 (0–19) | 2 (0–21) | 20 (0–81) |
|
| 30 (5.2) | 8.5 (1–121) | 3.5 (0–49) | 11 (0–374) | 18 (0–241) |
|
| 74 (12.9) | 14.5 (0–868) | 3 (0–62) | 7 (0–135) | 27 (0–1019) |
|
| 572 (100) | 19 (0–868) | 2 (0–235) | 9 (0–502) | 39.5 (0–1019) |
≠ The values were presented as median (minimum-maximum).
The articles with exposure social media were related to the higher citation rates.
| Median GS citations | Median WoS citations | ||
|---|---|---|---|
|
| No | 9 | 2 |
| Yes | 21 | 5 | |
|
| <0.001 | <0.001 | |
|
| No | 8 | 2 |
| Yes | 20 | 5 | |
|
| <0.001 | <0.001 |
GS: Google Scholar; WoS: Web of Science; SoMe: Social Media.
Fig 1The correlation between citation of articles, and metric value and Twitter posts.
A. The relationship between metric value of articles and Google scholar citations. B. The relationship between metric value of articles and Web of Science citations. C. The relationship between Twitter posts of articles and Web of Science citations. D. The relationship between Twitter posts of articles and Google Scholar citations.