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科学推文作者行为模式与地理分布研究 被引量:3

Study of Scientific Tweet Author's Behavior Pattern and Geographic Distribution
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摘要 通过对2069万多条科学推文的263万多位作者做统计分析和可视化分析,揭示了科学推文作者在发文量、关注来源和关注学科方面的行为模式,以及国家层次和城市层次的地理分布,为进一步理解推特替代计量指标内涵进而科学合理应用提供基础。研究发现:(1)科学推文作者的发文量分布存在显著的集中分布规律,10%的作者发表了80%的科学推文,91%的作者发表科学推文量在10条及以下,说明存在少数科学推文量极高的作者,同时大部分作者只是偶尔在推特上传播和讨论研究成果;(2)关注作者数最多的核心来源占6%,对应77%的科学推文,尤以Nature、The Conversation和PLo S ONE居前三甲,62%的作者仅关注一种来源;(3)关注作者数最多的学科分布在医学、综合科学和社会科学,71%的作者仅在一个学科里关注研究成果,8%的作者会关注3个以上学科的研究成果;(4)科学推文作者广泛分布在世界各地,尤以美国和欧洲最为密集,东亚集中在日本,南美集中在巴西,且集中分布在伦敦、纽约、多伦多等城市。这些结果表明,纯粹基于科学推文量的推特替代计量指标有失公允,未来构建实用指标时必须将作者情境作为要素纳入考虑范围。 Statistical and visualization analyses were conducted on 2.63 million authors of 20.69 million scientific tweets, to reveal the authors' behavior patterns including the number of scientific tweets, followed sources, and followed disciplines, as well as their geographic distribution at both a country and a city level. Results will provide reference for further understanding of the meaning of Twitter altmetrics and for future applications. Results show: (1) the distribution of authors' productivity is highly skewed; 10% of the authors produced 80% of scientific tweets, and 91% of the authors tweeted no more than 10 scientific tweets. This means that most authors only occasionally disseminate and discuss academic products on Twitter. Meanwhile, there is a small percentage of extremely active authors. (2) Core sources that attract most authors, such as Nature, The Conversation and PLoS ONE, take up 6% of all publication sources and account for 77% of scientific tweets. Furthermore, 62% of authors follow only one source. (3) Disciplines that attract most authors are Medicine, General and Social Science, with 71% of authors following only 1 discipline while approximately 8% of authors follow over 3 disciplines. (4) Authors of scientific tweets are distrib-uted all over the world, but are especially dense in USA and Europe. In East Asia, Japan is the most prominent country whereas in South America, Brazil is the most prominent. Authors are concentrated in cities like London and New York. These results show that Twitter altmetrics based on pure number of scientific tweets are not effective enough and future practical indicators need to combine author context as an important factor.
作者 余厚强 王曰芬 王菲菲 陈必坤 Yu Houqiang;Wang Yuefen;Wang Feifei;Chen Bikun(School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094;School of Economics and Management, Beijing University of Technology, Beijing 100124)
出处 《情报学报》 CSSCI CSCD 北大核心 2018年第2期140-150,共11页 Journal of the China Society for Scientific and Technical Information
基金 国家社会科学基金重大项目"面向知识创新服务的数据科学理论与方法研究"(16ZDA224) 江苏省高校优势学科建设工程资助项目
关键词 替代计量学 推特替代计量指标 微博替代计量指标 推特 作者分布 altmetrics Twitter altmetrics Microblog altmetrics Twitter author distribution
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