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[目的/意义]为了推动中国学者学术论文的国际影响力,有利于国内学者在发表国际论文时有更好的选择依据。[方法/过程]以2013—2019年Altmetric Top 100中国科学论文为研究样本,通过对其Altmetrics数据和传统计量数据进行统计,分析研究其特征。[结果/结论]论文聚焦于医学、生物和社会研究等学科,主要由中国科学院和国内985高校(双一流)研究完成,与欧美发达国家合作较多,主要发表于非付费获取方式的高影响因子国际期刊,一般由社会公众在Twitter上讨论与传播,其Altmetrics评分与被引频次的相关性极弱。 相似文献
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[目的/意义] 学者是学术知识的创造者,也是学术创新的主要推动者。学者学术影响力评价对学者学术发展具有导向作用,也是每位学者关注的焦点。[方法/过程] 本研究提出一种基于动态变化的学者学术影响力测度方法,以中国引文数据库（CCD）为统计工具,利用SIF测度模型对2019年爱思唯尔（Elsevier）发布的艺术和人文学科领域的中国高被引学者学术影响力演变进行分析。[结果/结论] 结果表明,SIF测度模型弥补了h指数在评价学者影响力的不足,对学者学术影响力演变测度具有适用性,揭示学者学术生涯的学术影响力演变过程。 相似文献
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《期刊图书馆员》2012,62(1-2):23-37
ABSTRACTLibrary and information science as a discipline is undergoing rapid and extensive change, driven particularly by new areas of research. Citation analysis and information literacy are widely researched and have a rich background of growth. Publish or Perish, Buzzsumo.com, altmetrics.com, and textalyser.net have been used to analyze all metrics associated with citation analysis, social networking, and keyword analysis.The hypothesis of this study is: “There is no significant difference in the citation pattern of the three prominent citation journals: Journal of Information Literacy, Communications in Information Literacy and Nordic Journal of Information Literacy in Higher Education”.The hypotheses of the study were tested by assessment of the degree to which each of the journals met set of objective criteria. 697 papers from the three journals were analyzed and the results showed that the citation metrics of the Journal of Information Literacy had the highest correspondence with the criteria. The information linked to the Journals of Information Literacy was moderately posted on social networking sites (SNS) and the highest frequency of the keywords: “Information”; “Information literacy”; and “Information literacy instruction” were found in one, two and three-word searches. Some recommendations have also been offered to improve SNS presence and for further research in this field. 相似文献
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Twitter altmetrics has been proposed to measure the popularity and the potential societal impact of scientific products, but scientific tweeters who produce the Twitter altmetrics data have not been well explored. The study, by analyzing 2.63 million scientific tweeters’ data that are extracted from the Altmetric.com company dataset, is aimed to reveal their productivity and geographic distribution in a comprehensive way. To gain a more in-depth understanding of their account types and identities, 1468 scientific tweeters of different levels of activeness are sampled for further analysis. Our results show that: (1) The extent to which a small proportion of tweeters have posted most of scientific tweets increases over time. In 2016, 10% of scientific tweeters have posted 80% of scientific tweets; (2) Scientific tweeters are widely distributed around the world but in a different pattern with the distribution of general Twitter users. In addition, scientific tweeters are found to be more active in tweeting scientific products than retweeting them in certain areas. (3) Manual coding of the sampled tweeters shows that the percentage of bot accounts among scientific tweeters is 1.8%, which is much lower than that among general Twitter users. Moreover, 73% of scientific tweeters use Twitter for professional purpose, 76% use real names for their accounts, and 16% are institutional accounts. (4) Identities of scientific tweeters are diversified. 49% of them are researchers among which university faculty is the major type, and 38% of them are the general public. With these results we suggest number of scientific tweets is not a good indicator of measuring either popularity or impact, tweeter’s productivity, location and identities must be taken into consideration in interpreting the meaning of Twitter altmetrics. 相似文献
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Online book reviews reflect readers’ attitudes and opinions and serve as a data source for book impact assessment. Most research has only focused on the number of ratings and reviews to assess the impact of books. However, it is necessary to more thoroughly explore online book reviews, to analyze the viewpoints and sentiments expressed in them and the identity and motivation of the reviewers in order to evaluate the value of different types of book reviews. In this study, we collect Goodreads reviews of books indexed by the Book Citation Index and consider them according to the following three aspects: the popularity of highly cited books in Goodreads, the influence of reviewer roles (of author, librarian, and ordinary user) on book reviews, and the emotions and opinions behind reviewers’ ratings. Results consider the number of books reviewed in different disciplines, the variations in ratings of highly cited and non-highly cited books, differences in book reviews given by the reviewer roles, and the way reviewers express their sentiments about the books. The study concludes that if online reviews are to be used as indicators of book impact assessment, key considerations should include the subject discipline, the reviewer's role, and the sentiment polarity. 相似文献
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作为衡量新型影响力的计量方法,Altmetrics的出现引起了科技评价领域的广泛讨论。研究影响高Altmetrics指标论文的特征因素及其演变情况,可为合理使用Altmetrics指标提供借鉴,为发展和完善Altmetrics计量方法提供参考。因此,本文选取Altmetric Top 100论文作为研究样本,对比分析2013-2018年6年的高Altmetrics指标论文的时间分布、期刊分布、研究领域分布以及多源指标贡献度的演变情况。研究结果表明,高Altmetrics指标论文的网络关注度大体上逐年上升,并主要发表在Nature、Science、PNAS等10种高影响力期刊上,分布于医学健康科学、生物科学等8个研究领域。在多项Altmetrics指标中,News、Blogs以及Twitter表现出显著优势。 相似文献
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在讨论OA论文影响的形成过程、影响因素和形成机制的基础上,本研究以中美学者发表在PLoS平台的7种OA期刊上的论文为样本,以PLoS Article-Level Metrics为工具,统计五大类指标(浏览下载量、引用量、保存量、讨论量、推荐量)的24个分指标数据,从指标相关性、不同年份、不同类型论文、不同分指标等方面,系统比较中美OA论文影响的异同。研究发现:①中美OA论文各指标间的相关性类似,被引量与浏览下载量有较高相关性,与讨论量相关性最弱。②总体上美国论文各指标值高于中国论文,讨论量、推荐量和浏览下载量相距较大,保存量则相差不大;只通过被引量衡量,低估了中美OA论文影响存在的差距。③中国论文中,中国作者为辅的论文影响指标值相对较高,中国独著的论文表现最差;美国论文中,美国作者为主的论文在多个指标值中最高。中美论文在不同分指标间也存在差异。图6。表6。参考文献50。 相似文献
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政策文件替代计量指标作为一种相对较新的指标,为测度学术成果的社会影响力提供了新方向,具有很高的研究价值。本文基于Altmetric.com公司从2013年1月到2016年6月收集到的所有政策文件替代计量指标数据9万余条,通过统计分析揭示其分布特征,旨在为进一步研究提供基础。研究发现,政策文件替代计量指标的相对覆盖率较低,为1.7%;相对引文指标没有及时性优势,平均时滞长达4.5年;论文层次的分布较为均匀,94%的学术成果仅有1条政策文件提及;期刊层次的分布基本遵循布拉德福定律,EFSA Journal等核心期刊是政策文件参考的主要学术成果来源;保健科学和医学是政策文件提及最多的学科,占据了“半边江山”;具有政策文件替代计量指标的学术成果,其替代计量关注度指数总体处于中等偏上水平,没有明显优势。图7。表5。参考文献19。 相似文献
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基于Altmetrics的学术论文影响力评价研究——以汉语言文学学科为例 总被引：2，自引：2，他引：0
本文借助Altmetric Explorer和SPSS统计分析软件获取和分析处理数据,综合运用相关性分析法和主成分分析法,对现有Altmetrics评价指标进行定量分析和选取,设计和构建基于Altmetrics的学术论文影响力评价框架及模型,并通过实证研究证明评价模型的可行性。通过与传统引文指标评价方法的对比分析,发现Altmetrics评价指标同传统的引文指标在评价结果上既具有一致性也存在差异,Altmetrics测度的影响力偏向社会影响力及社会关注度,较少涉及表征论文质量的学术影响力。基于Altmetrics的学术论文影响力评价对传统的基于文献计量学的学术论文影响力评价有所补充。图6。表12。参考文献15。 相似文献
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Recently, two new indicators (Equalized Mean-based Normalized Proportion Cited, EMNPC; Mean-based Normalized Proportion Cited, MNPC) were proposed which are intended for sparse scientometrics data, e.g., alternative metrics (altmetrics). The indicators compare the proportion of mentioned papers (e.g. on Facebook) of a unit (e.g., a researcher or institution) with the proportion of mentioned papers in the corresponding fields and publication years (the expected values). In this study, we propose a third indicator (Mantel-Haenszel quotient, MHq) belonging to the same indicator family. The MHq is based on the MH analysis – an established method in statistics for the comparison of proportions. We test (using citations and assessments by peers, i.e. F1000Prime recommendations) if the three indicators can distinguish between different quality levels as defined on the basis of the assessments by peers. Thus, we test their convergent validity. We find that the indicator MHq is able to distinguish between the quality levels in most cases while MNPC and EMNPC are not. Since the MHq is shown in this study to be a valid indicator, we apply it to six types of zero-inflated altmetrics data and test whether different altmetrics sources are related to quality. The results for the various altmetrics demonstrate that the relationship between altmetrics (Wikipedia, Facebook, blogs, and news data) and assessments by peers is not as strong as the relationship between citations and assessments by peers. Actually, the relationship between citations and peer assessments is about two to three times stronger than the association between altmetrics and assessments by peers. 相似文献