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| Distribution Features of Facebook Altmetrics of Scholarly Outputs |
| Yu Houqiang1,2, Zhang Wei2, Cao Xueting2 |
1.School of Information Management, Sun Yat-sen University, Guangzhou 510006
2.School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094 |
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Abstract In this paper, a statistical analysis of more than 420,000 Facebook altmetrics from July 2018 to June 2019 and a preliminary exploration of their numerical distribution characteristics were conducted. The study found that the relative coverage rate of Facebook altmetrics is 8.1%, indicating a relatively low level. The immediacy rate of Facebook altmetrics is 74%, which is better than News, Twitter, Weibo, and Policy document altmetrics, which instructs Facebook users to pay more attention to the latest achievements. The distribution of academic publications is relatively even: as based on the number of independent users, 20% of academic publications are mentioned by only 37% of Facebook altmetrics. The distribution of academic sources is in accordance with Bradford's Law, and 140 core sources are calculated, of which the core sources are The Conservation, Nature, and Science. As for the discipline-level distribution of Facebook altmetrics, medical and health sciences is in the dominant position, reaching as high as 61%, and biological science, psychology, and cognitive science also receive relatively high mentions. These conclusions will provide a reference for the further application of Facebook altmetrics.
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Received: 10 September 2020
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1 余厚强, 王曰芬, 王菲菲, 等. 科学推文作者行为模式与地理分布研究[J]. 情报学报, 2018, 37(2): 140-150.
2 Shu F, Lou W, Haustein S. Can Twitter increase the visibility of Chinese publications?[J]. Scientometrics, 2018, 116(1): 505-519.
3 Maflahi N, Thelwall M. How quickly do publications get read? The evolution of Mendeley reader counts for new articles[J]. Journal of the Association for Information Science and Technology, 2018, 69(1): 158-167.
4 刘晓娟, 周建华, 尤斌. 基于Mendeley与WoS的选择性计量指标与传统科学计量指标相关性研究[J]. 图书情报工作, 2015, 59(3): 112-118.
5 宋丽萍, 王建芳, 王树义. 科学评价视角下F1000、Mendeley与传统文献计量指标的比较[J]. 中国图书馆学报, 2014, 40(4): 48-54.
6 Bornmann L. Is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration? An analysis based on data from F1000Prime and normalized citation scores[J]. Journal of the Association for Information Science and Technology, 2017, 68(4): 1036-1047.
7 Siravuri H V, Alhoori H. What makes a research article newsworthy?[J]. Proceedings of the Association for Information Science and Technology, 2017, 54(1): 802-803.
8 王菲菲, 贾晨冉, 韩文菲, 等. 政策文件替代计量视角下的学术成果利用效率分布态势剖析[J]. 北京工业大学学报(社会科学版), 2018, 18(4): 55-66.
9 Shema H, Bar-Ilan J, Thelwall M. How is research blogged? A content analysis approach[J]. Journal of the Association for Information Science and Technology, 2015, 66(6): 1136-1149.
10 Kousha K, Thelwall M. An automatic method for assessing the teaching impact of books from online academic syllabi[J]. Journal of the Association for Information Science and Technology, 2016, 67(12): 2993-3007.
11 赵蓉英, 魏明坤, 汪少震. 基于Altmetrics的开源软件学术影响力评价研究[J]. 中国图书馆学报, 2017, 43(2): 80-95.
12 Bik H M, Goldstein M C. An introduction to social media for scientists[J]. PLoS Biology, 2013, 11(4): e1001535.
13 Bedrick S D, Sittig D F. A scientific collaboration tool built on the Facebook platform[J]. AMIA Annual Symposium Proceedings, 2008, 2008: 41-45.
14 Thelwall M, Haustein S, Larivière V, et al. Do altmetrics work? Twitter and ten other social web services[J]. PLoS One, 2013, 8(5): e64841.
15 Néda Z, Varga L, Biró T S. Science and Facebook: the same popularity law![J]. PLoS One, 2017, 12(7): e0179656.
16 Na J C, Ye Y E. Content analysis of scholarly discussions of psychological academic articles on Facebook[J]. Online Information Review, 2017, 41(3): 337-353.
17 Mohammadi E, Barahmand N, Thelwall M. Who shares health and medical scholarly articles on Facebook[J]. Learned Publishing, 2020, 33(2): 111-118.
18 Enkhbayar A, Alperin J P. Challenges of capturing engagement on Facebook for Altmetrics[C]// Proceedings of the 23rd International Conference on Science and Technology Indicators. Centre for Science and Technology Studies, 2018: 1460-1469.
19 Rousseau R. The Australian and New Zealand fields of research (FoR) codes[J]. ISSI Newsletter, 2018, 14(3): 59-61.
20 Yu H Q. Context of altmetrics data matters: an investigation of count type and user category[J]. Scientometrics, 2017, 111(1): 267-283.
21 Yu H Q, Xu S M, Xiao T T, et al. Global science discussed in local altmetrics: Weibo and its comparison with Twitter[J]. Journal of Informetrics, 2017, 11(2): 466-482.
22 余厚强, 曹雪婷, 王曰芬. 新闻替代计量指标的分布特征研究[J]. 情报学报, 2020, 39(10): 1081-1092.
23 余厚强, 肖婷婷, 王曰芬, 等. 政策文件替代计量指标分布特征研究[J]. 中国图书馆学报, 2017, 43(5): 57-69.
24 余厚强, HemmingerBradley M., 肖婷婷, 等. 新浪微博替代计量指标特征分析[J]. 中国图书馆学报, 2016, 42(4): 20-36.
25 Enkhbayar A, Haustein S, Barata G, et al. How much research shared on Facebook is hidden from public view? A comparison of public and private online activity around PLOS ONE papers[OL]. (2019-09-03). https://arxiv.org/vc/arxiv/papers/1909/1909.01476v1. pdf.
26 Fang Z C, Costas R. Studying the accumulation velocity of altmetric data tracked by Altmetric.com[J]. Scientometrics, 2020, 123(2): 1077-1101. |
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