Citation prediction of scholarly papers is of great significance in guiding funding allocations, recruitment decisions, and rewards. However, little is known about how citation patterns evolve over time. By exploring the inherent involution property in scholarly paper citation, we introduce the Paper Potential Index (PPI) model based on four factors: inherent quality of scholarly paper, scholarly paper impact decaying over time, early citations, and early citers' impact. In addition, by analyzing factors that drive citation growth, we propose a multi-feature model for impact prediction. Experimental results demonstrate that the two models improve the accuracy in predicting scholarly paper citations. Compared to the multi-feature model, the PPI model yields superior predictive performance in terms of range-normalized RMSE. The PPI model better interprets the changes in citation, without the need to adjust parameters. Compared to the PPI model, the multi-feature model performs better prediction in terms of Mean Absolute Percentage Error and Accuracy; however, their predictive performance is more dependent on the parameter adjustment.
Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order depen…
Books have been widely used to share information and contribute to human knowledge. However, the quantitative use of books as a method of scholarly communication is relatively unexamined compared to journal articles and conference papers. This study uses the COCI dataset (a comprehensive open citation dataset provided by OpenCitations) to explore books' roles in scholarly communication. The COCI data we analyzed includes 445,826,118 citations from 46,534,705 bibliographic entities. By analyzing such a large amount of data, we provide a thorough, multifaceted understanding of books. Among the i…
One of the main indicators of scientific development of a given country is the number of papers published in high impact scholarly journals. Many countries introduced performance-based research funding systems (PRFSs) to create a more competitive environment where prolific researchers get rewarded with subsidies to increase both the quantity and quality of papers. Yet, subsidies do not always function as a leverage to improve the citation impact of scholarly papers. This paper investigates the effect of the publication support system of Turkey (TR) on the citation impact of papers authored by …
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…
In this work, we try to answer the question of which method, peer review vs bibliometrics, better predicts the future overall scholarly impact of scientific publications. We measure the agreement between peer review evaluations of Web of Science indexed publications submitted to the first Italian research assessment exercise and long-term citations of the same publications. We do the same for an early citation-based indicator. We find that the latter shows stronger predictive power, i.e., it more reliably predicts late citations in all the disciplinary areas examined, and for any citation time…
Understanding how a scientist develops new scientific collaborations or how their papers receive new citations is a major challenge in scientometrics. The approach being proposed simultaneously examines the growth processes of the co-authorship and citation networks by analyzing the evolutions of the rich get richer and the fit get richer phenomena. In particular, the preferential attachment function and author fitnesses, which govern the two phenomena, are estimated non-parametrically in each network. The approach is applied to the co-authorship and citation networks of the flagship journal o…
Beyond citations: Scholars' visibility on the social Web
传统上，学术影响力和知名度是通过计算学术文献中的出版物和引用来衡量的。然而，越来越多的学者也出现在网络上，在越来越多的社会生态系统中建立存在。但是，这种存在有多广泛，有多成熟，社交网络影响的衡量标准与传统的衡量标准有什么关系？为了回答这个问题，我们从2010年莱顿STI会议上抽样调查了57位演讲者，收集了他们的出版物和引用次数，以及演讲者的网络足迹数据。“我们发现网络存在广泛而多样：84%的学者有主页，70%在LinkedIn上，23%有公开的Google Scholar个人资料，16%在Twitter上。对于抽样学者的出版物，社会参考管理器书签进行了比较，Scopus和Web of Science引文;我们发现，Mendeley涵盖了80%以上的抽样文章，Mendeley书签显着相关（r= 0.45）Scopus引用计数。
How common is self-citation in scholarly publication, and does the practice vary by gender? Using novel methods and a data set of 1.5 million research papers in the scholarly database JSTOR published between 1779 and 2011, the authors find that nearly 10 percent of references are self-citations by a paper's authors. The findings also show that between 1779 and 2011, men cited their own papers 56 percent more than did women. In the last two decades of data, men self-cited 70 percent more than women. Women are also more than 10 percentage points more likely than men to not cite their own previou…
As part of its scholarly data efforts, the Internet Archive (IA) releases a first version of a citation graph dataset, named refcat, derived from scholarly publications and additional data sources. It is composed of data gathered by the fatcat cataloging project (the catalog that underpins IA Scholar), related web-scale crawls targeting primary and secondary scholarly outputs, as well as metadata from the Open Library project and Wikipedia. This first version of the graph consists of over 1.3B citations. We release this dataset under a CC0 Public Domain Dedication, accessible through Internet …
Dissertations can be the single most important scholarly outputs of junior researchers. Whilst sets of journal articles are often evaluated with the help of citation counts from the Web of Science or Scopus, these do not index dissertations and so their impact is hard to assess. In response, this article introduces a new multistage method to extract Google Scholar citation counts for large collections of dissertations from repositories indexed by Google. The method was used to extract Google Scholar citation counts for 77,884 American doctoral dissertations from 2013-2017 via ProQuest, with a …
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…
A crucial goal of funding research and development has always been to advance economic development. On this basis, a consider-able body of research undertaken with the purpose of determining what exactly constitutes economic impact and how to accurately measure that impact has been published. Numerous indicators have been used to measure economic impact, although no single indicator has been widely adapted. Based on patent data collected from Altmetric we predict patent citations through various social media features using several classification models. Patents citing a research paper implies …
Unraveling the Ai2 Asta Scholarly Research Assistant Citation System
The iMetrics Lab. Department of Audiovisual Communication, Documentation and History of Art, Universitat Politècnica de València（瓦伦西亚理工大学）；Departament de Biblioteconomia, Documentació i Comunicació Audiovisual, Universitat de Barcelona（巴塞罗那大学）
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 explores, by using suitable quantitative techniques, to what extent the intellectual proximity among scholarly journals is also a proximity in terms of social communities gathered around the journals. Three fields are considered: statistics, economics and information and library sciences. Co-citation networks (CC) represent the intellectual proximity among journals. The academic communities around the journals are represented by considering the networks of journals generated by authors writing in more than one journal (interlocking authorship: IA), and the networks generated by scho…
Altmetrics from Altmetric.com are widely used by publishers and researchers to give earlier evidence of attention than citation counts. This article assesses whether Altmetric.com scores are reliable early indicators of likely future impact and whether they may also reflect non-scholarly impacts. A preliminary factor analysis suggests that the main altmetric indicator of scholarly impact is Mendeley reader counts, with weaker news, informational and social network discussion/promotion dimensions in some fields. Based on a regression analysis of Altmetric.com data from November 2015 and Scopus …
Identifying important scholarly literature at an early stage is vital to the academic research community and other stakeholders such as technology companies and government bodies. Due to the sheer amount of research published and the growth of ever-changing interdisciplinary areas, researchers need an efficient way to identify important scholarly work. The number of citations a given research publication has accrued has been used for this purpose, but these take time to occur and longer to accumulate. In this article, we use altmetrics to predict the short-term and long-term citations that a s…
Eugene Garfield's Scholarly Impact: A Scientometric Review
引文索引的概念已经深入到研究本身的许多部分以及研究发挥不可或缺作用的广泛环境中，从研究评估，众多指标到越来越广泛的科学学科。在这篇文章中，我们向尤金·加菲尔德致敬，并对他带给我们的智力资产进行了科学计量学回顾。此外，我们探讨了知识景观，随后演变连接到他的许多想法。我们说明了科学文献的系统综述可能揭示什么，以及我们可以从通过引用诱导模式传达的丰富信息中学到什么。这项研究是由CiteSpace进行的，CiteSpace是基于Web of Science和Scopus数据的众多科学绘图工具之一。如果没有加菲尔德的发明，这些都不可能实现。
Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；University of Stuttgart（斯图加特大学）
Citation information in scholarly data is an important source of insight into the reception of publications and the scholarly discourse. Outcomes of citation analyses and the applicability of citation based machine learning approaches heavily depend on the completeness of such data. One particular shortcoming of scholarly data nowadays is that non-English publications are often not included in data sets, or that language metadata is not available. Because of this, citations between publications of differing languages (cross-lingual citations) have only been studied to a very limited degree. In…
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…
Measuring research impact is important for ranking publications in academic search engines and for research evaluation. Social media metrics or altmetrics measure the impact of scientific work based on social media activity. Altmetrics are complementary to traditional, citation-based metrics, e.g. allowing the assessment of new publications for which citations are not yet available. Despite the increasing importance of altmetrics, their characteristics are not well understood: Until now it has not been researched what kind of researchers are actively using which social media services and why -…
In this article, we focus on the importance of open research information as the foundation for transparent and responsible research assessment and discovery of research outputs. We introduce work in which we support the open research information commons by enabling, in particular, independent and small Open Access journals to provide metadata to several open data hubs (Open Citations, Wikidata, Open Research Knowledge Graph). In this context, we present The OPTIMETA Way, a means to integrate metadata collection, enrichment, and distribution in an effective and quality-ensured way that enables …
Science is a cumulative activity, which can manifest itself through the act of citing. Citations are also central to research evaluation, thus creating incentives for researchers to cite their own work. Using a dataset containing more than 63 million articles and 51 million disambiguated authors, this paper examines the relative importance of self-citations and self-references in the scholarly communication landscape, their relationship with the age and gender of authors, as well as their effects on various research evaluation indicators. Results show that self-citations and self-references ev…
The need for scholarly open data is ever increasing. While there are large repositories of open access articles and free publication indexes, there are still a few examples of free citation networks and their coverage is partial. One of the results is that most of the evaluation processes based on citation counts rely on commercial citation databases. Things are changing under the pressure of the Initiative for Open Citations (I4OC), whose goal is to campaign for scholarly publishers to make their citations as totally open. This paper investigates the growth of open citations with an experimen…
Knowledge graphs represent the meaning of properties of real-world entities and relationships among them in a natural way. Exploiting semantics encoded in knowledge graphs enables the implementation of knowledge-driven tasks such as semantic retrieval, query processing, and question answering, as well as solutions to knowledge discovery tasks including pattern discovery and link prediction. In this paper, we tackle the problem of knowledge discovery in scholarly knowledge graphs, i.e., graphs that integrate scholarly data, and present Korona, a knowledge-driven framework able to unveil scholar…
It is a matter of debate whether a shrinking proportion of scholarly literature is getting most of the references over time. It is also less well understood how a narrowing literature usage would affect the circulation of ideas in the sciences. Here we show, that the utilization of scientific literature follows dual tendencies over time: while a larger proportion of literature is cited at least a few times, citations are also concentrating more on the top of the citation distribution. Parallel to the latter trend, a paper's future importance increasingly depends on its past citation performanc…
How Proposal Novelty, Topical Diversity, and Theory-Practice Balance Shape Scholarly Outcomes in Funded Education Research
School of Economics and Management, East China Normal University（华东师范大学经济与管理学院）；Department of Education, Amity Global Institute（Amity全球学院教育学系）；School of Mathematics and Statistics, The University of Glasgow（格拉斯哥大学数学与统计学院）；Business School, The University of Edinburgh（爱丁堡大学商学院）
The rapid evolution of scientific research has been creating a huge volume of publications every year. Among the many quantification measures of scientific impact, citation count stands out for its frequent use in the research community. Although peer review process is the mainly reliable way of predicting a paper's future impact, the ability to foresee lasting impact on the basis of citation records is increasingly important in the scientific impact analysis in the era of big data. This paper focuses on the long-term citation count prediction for individual publications, which has become an e…
Dimensions is a partly free scholarly database launched by Digital Science in January 2018. Dimensions includes journal articles and citation counts, making it a potential new source of impact data. This article explores the value of Dimensions from an impact assessment perspective with an examination of Food Science research 2008-2018 and a random sample of 10,000 Scopus articles from 2012. The results include high correlations between citation counts from Scopus and Dimensions (0.96 by narrow field in 2012) as well as similar average counts. Almost all Scopus articles with DOIs were found in…
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。
