In a study of articles published in the Proceedings of the National Academy of Sciences, Gunther Eysenbach discovered a significant citation advantage for those articles made freely-available upon publication (Eysenbach 2006). While the author attempted to control for confounding factors that may have explained the citation differential, the study was unable to control for characteristics of the article that may have led some authors to pay the additional page charges ($1,000) for immediate OA status. OA articles published in PNAS were more than twice as likely to be featured on the front cover of the journal (3.3% vs. 1.4%), nearly twice as likely to be picked up by the media (15% vs. 8%) and when cited reached, on average, nearly twice as many news outlets as subscription-based articles (4.2 vs. 2.6). The citation advantage of Open Access articles in PNAS may likely be explained by a quality differential and the amplification of media effects.
Altmetrics in the wild: Using social media to explore scholarly impact
越来越多的学者将博客、Twitter和Mendeley等社交媒体工具整合到他们的专业交流中。这些工具的在线和公共性质暴露并具体化了曾经隐藏和短暂的学术过程。基于这些活动的数据库可以为更广泛、更快的影响力衡量提供信息，补充传统的引文指标。这项研究探讨了这些基于社交媒体的指标或“altmetrics”的属性，对公共科学图书馆发表的24，331篇文章进行了抽样。我们发现，不同的指标有很大的不同活动。大约5%的样本文章被维基百科引用，而近80%的文章被至少一个Mendeley图书馆收录。然而，有一个令人鼓舞的多样性;四分之一的文章有来自五个或更多不同来源的非零数据。相关性和因子分析表明，引用和altmetrics指标跟踪相关但不同的影响，两者都不能单独描述学术使用的全貌。Mendeley和Web of Science引用之间存在中度相关性，但许多altmetric指标似乎主要与引用正交。文章以五种不同的影响“口味”的方式聚集，捕捉不同类型对不同受众的影响;例如，一些文章可能被学者大量阅读和保存，但很少被引用。总之，这些发现鼓励更多的研究altmetrics作为补充，传统的引文措施。
This paper presents the results of a systematic review of the literature on the impact of social media in learning and teaching through bibliometric based Citation analysis. The objective of the review was to map the evolution of the current literature and identify the leading sources of knowledge in terms of the most influential journals, authors, and articles. From a total of 50 top most relevant articles selected from the Scopus database, a detailed citation analysis was conducted. The study explored the overall theoretical foundation of social media research involving in learning and study…
Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature
社交媒体平台收集的数据最近被引入作为一个新的指标来源，以帮助衡量学术研究的影响，补充传统的基于引用的指标。与学术内容相关的社交媒体活动产生的数据可用于反映广泛类型的影响。本文旨在提供有关Twitter被用于传播生物医学和生命科学期刊文章的频率的系统性证据。该分析基于PubMed和Web of Science（WoS）涵盖的一组140万份文件，并在2010年至2012年期间发表。分析了包含这些文件链接的推文数量，以评估某些期刊，学科和专业在Twitter上的代表程度。它表明，只有不到10%的PubMed文章在Twitter上被提及，其吸收率一般较低。tweets和WoS引用之间的关系进行了检查，为每个文件在期刊和专业的水平。研究结果表明，不同期刊和专业的研究者的推文行为存在差异，推文与引文之间的相关性较低，这意味着基于推文的影响力指标与基于引文的影响力指标存在差异。一个框架，利用覆盖的文章和Twitter的提及和引用之间的相关性，提出了促进新的基于社交媒体的指标的评估，并阐明了在多大程度上的推文的数量是一个有效的指标来衡量研究的影响力的问题。
This paper measures social media activity of 15 broad scientific disciplines indexed in Scopus database using Altmetric.com data. First, the presence of Altmetric.com data in Scopus database is investigated, overall and across disciplines. Second, the correlation between the bibliometric and altmetric indices is examined using Spearman correlation. Third, a zero-truncated negative binomial model is used to determine the association of various factors with increasing or decreasing citations. Lastly, the effectiveness of altmetric indices to identify publications with high citation impact is com…
The study of how science is discussed and how scholarly actors interact on social media has increasingly become popular in the field of scientometrics in recent years. While most prior studies focused on research outputs discussed on global platforms, such as Twitter or Facebook, the presence of scholarly journals on local platforms was seldom studied, especially in the Chinese social media context. To fill this gap, this study investigates the uptake of WeChat (a Chinese social network app) by the Chinese scholarly journals indexed by the Chinese Social Sciences Citation Index (CSSCI). The re…
Scientific collaboration is often not perfectly reciprocal. Scientifically strong countries/institutions/laboratories may help their less prominent partners with leading scholars, or finance, or other resources. What is interesting in such type of collaboration is that (1) it may be measured by bibliometrics and (2) it may shed more light on the scholarly level of both collaborating organizations themselves. In this sense measuring institutions in collaboration sometimes may tell more than attempts to assess them as stand-alone organizations. Evaluation of collaborative patterns was explained …
A new methodology is proposed for comparing Google Scholar (GS) with other citation indexes. It focuses on the coverage and citation impact of sources, indexing speed, and data quality, including the effect of duplicate citation counts. The method compares GS with Elsevier's Scopus, and is applied to a limited set of articles published in 12 journals from six subject fields, so that its findings cannot be generalized to all journals or fields. The study is exploratory, and hypothesis generating rather than hypothesis-testing. It confirms findings on source coverage and citation impact obtained…
Many factors could affect the number of citations to a paper. Citations have an important role in research policy and in measuring the excellence of research and researchers. This work is the first study in software engineering (SE) to assess multiple factors affecting the number of citations to SE papers. We use (a) negative binomial regression and (b) quantile regression to study arithmetic mean and median expected citations of a paper. Our dataset includes all the 25,113 papers which have been published in a set of 16 main SE journals, between 1970 and 2018. Our results indicate that public…
Citation metrics are analytic measures used to evaluate the usage, impact and dissemination of scientific research. Traditionally, citation metrics have been independently measured at each level of the publication pyramid, namely at the article-level, at the author-level, and at the journal-level. The most commonly used metrics have been focused on journal-level measurements, such as the Impact Factor and the Eigenfactor, as well as on researcher-level metrics like the Hirsch index (h-index) and i10 index. On the other hand, reliable article-level metrics are less widespread, and are often res…
University of Manchester（曼彻斯特大学）；Idiap Research Institute（伊迪亚普研究所）
Diagrams are often used in scholarly communication. We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers of citations after 3 years. Inclusion of over three diagrams in this 8-page limit conference was found to correlate with a lower citation count. Focusing on neural network system diagrams, we find a correlation between highly cited papers and "good diagramming practice" quantified by level of compliance with a set of diagramming guidelines. Two diagram class…
Predatory journals are Open Access journals of highly questionable scientific quality. Such journals pretend to use peer review for quality assurance, and spam academics with requests for submissions, in order to collect author payments. In recent years predatory journals have received a lot of negative media. While much has been said about the harm that such journals cause to academic publishing in general, an overlooked aspect is how much articles in such journals are actually read and in particular cited, that is if they have any significant impact on the research in their fields. Other stu…
Academic citation and social attention measure different dimensions of the impact of research results. Both measures do not correlate with each other, and they are influenced by many factors. Among these factors are the field of research, the type of access, and co-authorship. In this study, the increase in the impact due to co-authorship in scientific articles disaggregated by field of research and access type, was quantified. For this, the citations and social attention accumulated until the year 2021 by a total of 244,880 research articles published in the year 2018, were analyzed. The data…
ChatGPT cites the most-cited articles and journals, relying solely on Google Scholar's citation counts. As a result, AI may amplify the Matthew Effect in environmental science
Charles University（查理大学）；OpenAI, Inc（OpenAI公司）
本研究通过让 ChatGPT 撰写环境科学子学科综述并分析其参考文献，发现其仅依赖 Google Scholar 引用次数而倾向引用高被引、较早且发表于顶级期刊的文献，从而可能加剧科学引用中的马太效应。
In this study we analyse the key driving factors of preprints in enhancing scholarly communication. To this end we use four groups of metrics, one referring to scholarly communication and based on bibliometric indicators (Web of Science and Scopus citations), while the others reflect usage (usage counts in Web of Science), capture (Mendeley readers) and social media attention (Tweets). Hereby we measure two effects associated with preprint publishing: publication delay and impact. We define and use several indicators to assess the impact of journal articles with previous preprint versions in a…
Proper citation is of great importance in academic writing for it enables knowledge accumulation and maintains academic integrity. However, citing properly is not an easy task. For published scientific entities, the ever-growing academic publications and over-familiarity of terms easily lead to missing citations. To deal with this situation, we design a special method Citation Recommendation for Published Scientific Entity (CRPSE) based on the cooccurrences between published scientific entities and in-text citations in the same sentences from previous researchers. Experimental outcomes show th…
This paper opens by introducing the Internet Plus Government (IPG), a new government initiative emerging in the last decade. To understand benefits and challenges associated with this initiative worldwide, we conducted analyses on research articles published in the e-governance area between 2008 and 2017. Content analysis and citation analysis were performed on 2105 articles to address three questions: (1) What types of new ICT have been adopted in the IPG initiative in the past decade? (2) How did scholars investigate interactions between the new ICTs and governance core to IPG? (3) How did t…
In order to better understand the effect of social media in the dissemination of scholarly articles, employing the daily updated referral data of 110 PeerJ articles collected over a period of 345 days, we analyze the relationship between social media attention and article visitors directed by social media. Our results show that social media presence of PeerJ articles is high. About 68.18% of the papers receive at least one tweet from Twitter accounts other than @PeerJ, the official account of the journal. Social media attention increases the dissemination of scholarly articles. Altmetrics coul…
In the last two decades, scholars have designed various types of bibliographic related indicators to identify breakthrough-class academic achievements. In this study, we take a further step to look at properties of the promising disruptive index, thus deepening our understanding of this index and further facilitating its wise use in bibliometrics. Using publication records for Nobel laureates between 1900 and 2016, we calculate the DI of Nobel Prize-winning articles and its benchmark articles in each year and use the median DI to denote the central tendency in each year, and compare results be…
Social media platforms have now emerged as an important medium for wider dissemination of research articles; with authors, readers and publishers creating different kinds of social media activity about the article. Some research studies have even shown that articles that get more social media attention may get higher visibility and citations. These factors are now persuading journal publishers to integrate social media plugins in their webpages to facilitate sharing and dissemination of articles in social media platforms. Many past studies have analyzed several factors (like journal impact fac…
This literature review identifies indicators that associate with higher impact or higher quality research from article text (e.g., titles, abstracts, lengths, cited references and readability) or metadata (e.g., the number of authors, international or domestic collaborations, journal impact factors and authors' h-index). This includes studies that used machine learning techniques to predict citation counts or quality scores for journal articles or conference papers. The literature review also includes evidence about the strength of association between bibliometric indicators and quality score …
