|
|
|
| Distribution Features of News Altmetrics |
| Yu Houqiang1,2, Cao Xueting1, Wang Yuefen1 |
1.School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094
2.Jiangsu Collaborative Innovation Center of Social Safety Science and Technology, Nanjing 210094 |
|
|
|
|
Abstract Propagation tracing of scholarly output in news has provided the basis for news altmetrics. The latest research shows that news altmetrics could reflect the societal impact of scholarly output. This study systematically revealed the distribution features of news altmetrics based on statistical and comparative analysis of over 4.27 million news altmetrics data records. The results showed that comprehensive and medical news platforms mentioned the highest number of scholarly outputs, the top three being The Conversation, EurekAlert!, and MedicalXpress. News altmetrics had a 56% immediacy rate, higher than that of policy document altmetrics but lower than that of Weibo and Twitter altmetrics. Distribution at the article level was highly concentrated, as measured by the number of unique users; 20% of the scholarly outputs analyzed contributed to 65% of news mentions, with 3.5 news mentions on average. Distribution at the source level was in accordance with Bradford??s law; 76 core sources were identified, the top three being The Conversation, Nature, and PLoS ONE. At the disciplinary level, medical and health sciences dominates the distribution, followed by biological science and psychology and cognitive sciences. The results of this study will help researchers better comprehend and apply news altmetrics.
|
|
Received: 09 May 2019
|
|
|
|
1 Ravenscroft J, Liakata M, Clare A, et al. Measuring scientific impact beyond academia: An assessment of existing impact metrics and proposed improvements[J]. PLoS ONE, 2017, 12(3): e0173152.
2 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.
3 Shu F, Lou W, Haustein S. Can Twitter increase the visibility of Chinese publications?[J]. Scientometrics, 2018, 116(1): 505-519.
4 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.
5 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.
6 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.
7 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.
8 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.
9 Kousha K, Thelwall M, Abdoli M. The role of online videos in research communication: A content analysis of YouTube videos cited in academic publications[J]. Journal of the American Society for Information Science and Technology, 2012, 63(9): 1710-1727.
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 Thelwall M, Kousha K. ResearchGate articles: Age, discipline, audience size, and impact[J]. Journal of the Association for Information Science and Technology, 2017, 68(2): 468-479.
12 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.
13 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.
14 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.
15 余厚强. 替代计量指标与引文量相关性的大规模跨学科研 究——数值类型、指标种类与用户类别的影响[J]. 情报学报, 2017, 36(6): 606-617.
16 Wooldridge J, King M B. Altmetric scores: An early indicator of research impact[J]. Journal of the Association for Information Science and Technology, 2019, 70(3): 271-282.
17 Zheng H, Aung H H, Erdt M, et al. Social media presence of scholarly journals[I]. Journal of the Association for Information Science and Technology, 2019, 70(3): 256-270.
18 夏登武. 媒介融合环境下“小众学术”走进“大众视野”的策略研究[J]. 宁波大学学报(人文科学版), 2014, 27(2): 118-121.
19 Shoemaker P J. News and newsworthiness: A commentary[J]. Communications, 2006, 31(1): 105-111.
20 Lee S K, Lindsey N J, Kim K S. The effects of news consumption via social media and news information overload on perceptions of journalistic norms and practices[J]. Computers in Human Behavior, 2017, 75: 254-263.
21 Chang Y D. Science news release and its benefits to your research[J]. World Journal of Gastroenterology, 2007, 13(45): 6120-6121.
22 Dudo A. Scientists, the media, and the public communication of science[J]. Sociology Compass, 2015, 9(9): 761-775.
23 National Science Board. Science and technology: Public attitudes and understanding[EB/OL]. [2019-01-09]. http://www.nsf.gov/statistics/seind04/c7/c7s2.htm.
24 翟杰全. 国内科技传播研究:三大方向与三大问题[J]. 自然辩证法研究, 2007, 23(8): 68-71.
25 Kamenova K. Media portrayal of stem cell research: Towards a normative model for science communication[J]. Asian Bioethics Review, 2017, 9(3): 199-209.
26 Phillips D P, Kanter E J, Bednarczyk B, et al. Importance of the Lay Press in the transmission of medical knowledge to the scientific community[J]. The New England Journal of Medicine, 1991, 325(16): 1180-1183.
27 Kiernan V. Diffusion of news about research[J]. Science Communication, 2003, 25(1): 3-13.
28 高健, 陈新石, 游苏宁. 应充分利用大众媒体宣传科技期刊[J]. 编辑学报, 2008, 20(3): 235-237.
29 王大鹏, 钟琦, 王艳丽. 打通科研论文和科学报道之间的障 碍——以“刊媒惠”活动为例[J]. 科技传播, 2017, 9(17): 18-22.
30 余厚强, 尹梓涵, 李龙飞, 等. 基于案例分析的替代计量数据之科学使用方式研究[J]. 农业图书情报, 2019, 31(5): 21-27.
31 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.
32 Gamble J M, Traynor R L, Gruzd A, et al. Measuring the impact of pharmacoepidemiologic research using altmetrics: A case study of a CNODES drug-safety article[J]. Pharmacoepidemiology and Drug Safety, 2018, 29: 93-102.
33 金玲, 周玲, 林征, 等. 学术期刊全媒体科学普及传播实践[J]. 中国科技期刊研究, 2018, 29(2): 184-188.
34 邱均平, 余厚强. 论推动替代计量学发展的若干基本问题[J]. 中国图书馆学报, 2015, 41(1): 4-15.
35 Palmer S E, Schibeci R A. What conceptions of science communication are espoused by science research funding bodies?[J]. Public Understanding of Science, 2014, 23(5): 511-527.
36 余厚强, HemmingerB 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.
37 Yu H Q. Context of altmetrics data matters: An investigation of count type and user category[J]. Scientometrics, 2017, 111(1): 267-283.
38 Vickery B C. Bradford??s law of scattering[J]. Journal of Documentation, 1948, 4(3): 198-203.
39 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.
40 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. |
|
|
|
