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Data sharing and reuse promise many benefits to science, but many researchers are reluctant to share and reuse data. Data papers, published as peer‐reviewed articles that provide descriptive information about specific datasets, are a potential solution as they may incentivize sharing by providing a mechanism for data producers to get citation credit and support reuse by providing contextual information about dataset production. Data papers can receive many citations. However, does citation of a data paper mean reuse of the underlying dataset? This paper presents preliminary findings from a content‐based citation analysis of data papers (n = 103) published in two specialized data journals, one in earth sciences and one in physical and chemical sciences. We conclude that while the genre of data papers facilitates some data sharing and reuse, they fail to live up to their full potential. Further, practices of reuse of datasets from data papers vary considerably between disciplines. We propose measures for academic publishers to enhance the data paper's role in scholarly communication to attract more attention from researchers and to inform discipline‐specific policy and practices related to data publication. [ABSTRACT FROM AUTHOR]

Citations between papers and patents indicate knowledge transfer between science and technology. This study discusses the function of paper‐to‐patent citations through citation contexts. 7,223 articles having at least one paper‐to‐patent citation are identified from a collection of 2.4 million PubMed Central open access articles. Within 429,698 references cited by the 7,223 articles, 11,165 (2.6%) are paper‐to‐patent citations, while 418,533 (97.4%) are paper‐to‐paper citations. In comparison to paper‐to‐paper citations, paper‐to‐patent citations were more concentrated at the beginning of articles. Higher proportions of patents are cited in the introduction and methods sections and are only cited once. The results indicate that patents are likely to be cited for providing background knowledge. The appearance of paper‐to‐patent citations in the method sections implies that patents might also contribute to the development of research methods. [ABSTRACT FROM AUTHOR]

This study investigated papers posted on bioRXiv. In 2013–19, 17,818 papers were published in academic journals, accounting for 40.67% of the total publication. Among them, the Web of Science (WoS) Core Collection recorded journals of 16,525 published papers, accounting for 92.74% of the total. The following conclusions can be drawn. (1) Results indicate scientists' attention to the preprint system. (2) A large number of papers still use traditional publishing as the ultimate goal. (3) Because the posted papers scrutinized in this study were published in journals with a high impact factor, they have attracted the attention of many scientists. Nevertheless, we believe that the preprint platform will play a greater role from the academic exchange perspective. [ABSTRACT FROM AUTHOR]

Recently, open access has gradually become an important publishing model in scientific research, while the academic purification effect of open access on flawed publications needs to be further explored. In this study, we use the methods of entropy balancing matching (EBM) and difference in difference (DID) in causal inference to examine the academic purification effect of different open access levels. The results show that in the retraction speed, limited open access papers had the slowest retraction speed, non‐open access had the second and full open access had the fastest, reflecting the best performance of full open access in the detection of problematic papers. As for post‐retraction citation changes, the citation of limited open access papers declined slightly slower than that of non‐open access papers after retraction, while the citation of full open access papers showed an increase rather than a decrease. The next step of the research is to discover what factors may cause the above results. [ABSTRACT FROM AUTHOR]

This paper proposes an indicator for measuring the level of commitment to academic journals. The indicator is demonstrated on a sample of core LIS‐journals. By monitoring authorship patterns over a 20‐year period, it is shown that some journals have a higher frequency of returning authors than others, consequently showing a larger degree of community commitment. The paper discusses how the indicator may be applied when studying factors influencing researchers' journal selection decisions. [ABSTRACT FROM AUTHOR]

Peer review can evaluate the quality of academic articles involving the evaluation of some aspects, e.g., methodology, experiment, and aspects are usually the critical sections, substance and properties of the article concerned by reviewers. Previous research on content mining of peer review did not distinguish the round of reviews. Detecting differences peer review comments among different rounds can help us to understand the focus change of the reviewers in the different rounds. This paper takes the Nature Communications as an example to build the corpora of peer reviews in multiple rounds. We correlate review rounds and citations and extract aspects from the corpora to analyze the round characteristics of review comments. We find that there is no significant correlation between the review rounds and the citations frequency, but when the number of rounds is within 1–3, there is a weak positive correlation between the review rounds and citations. Additionally, the reviewers tend to pay more attention to the results analysis and the significance of the work firstly, and then they will focus on the details of the article, such as diagrams. This study can provide new ideas for peer review mining and the application of bibliometrics. [ABSTRACT FROM AUTHOR]

This study examines the relation between acceptance times in preprint publishing and journal publishing. Specifically, we investigated the association between a paper's posting time to bioRχiv, a preprints server, and journal articles' peer‐review and acceptance time for PLOS ONE. So far, of the total papers published in 1,626 academic journals, the average publication rate of those posted in bioRχiv is 40.67%. Meanwhile, PLOS ONE was the journal that published more papers. Analysis of peer‐review and acceptance time of papers published in journals via preprints showed the time these papers are posted in relation to these intervals. The median of the peer‐review and acceptance time of the journal submission date that was later than the date of first posting to bioRχiv was 110.00 days, and in the reverse case, it was 139.50 days. Posting to the preprint server before journal submission shows a better order than vice versa. This study provides us a good understanding of the peer‐review process. It also gives us good insights into optimizing this process, which would then facilitate paper publication and knowledge dissemination. [ABSTRACT FROM AUTHOR]

The Journal of the Association for Information Science & Technology (JASIST) is a leading information science journal, recognized by many ranking metrics. Understanding patterns in articles published would be helpful to new researchers seeking to publish with the journal. However, the last comprehensive bibliometric analysis on JASIST is more than a decade old. The objective of this paper is to analyze the bibliographic information of full‐length research articles published in JASIST during the last two decades. This includes metrics such as article count, authorship, international collaboration, citations, and topical areas. Data was collected from SCOPUS, JASIST website, and Scimago. The findings show that JASIST published 3,052 articles during 2000–2020, which got cited 180,608 times (59.18 times per article) to date. Joint authorship and international collaboration has been increasing. Authors from institutions in 70 countries have published, with most articles from USA, with authorship from China steadily increasing in recent years. The detailed findings in the paper would help information science researchers and practitioners to assess the areas of focus, and various patterns in a top journal of the field. Such historical understanding is critical in charting agendas and directions for future research. [ABSTRACT FROM AUTHOR]

Based on publications in Chemistry in 2015, this paper investigated the citation impact on domestic and foreign scholarly communities of Chinese and US publications, and to what extent does such impact relate to international collaboration and government funding. First‐ or corresponding authorship in international collaboration is defined as dominance and is taken into consideration. Citations to publications are designated as domestic citations (Chinese or US citations), partner citations or other citations according to overlap of countries of citing and cited publications. Significant difference exists in the two countries. Most citations of Chinese publications are from domestic and partner countries, with domestic citations being the mainstay. In contrast, US papers receive more other citations than domestic or partner citations, and citations from partner countries contribute significantly. US papers have higher global impact than those of China. High domestic citation propensity is associated with non‐international collaboration, dominance of focal country in international collaboration, and national funding support. Such phenomenon is more pronounced in Chinese papers. In other words, citation impact of Chinese publications is more limited in domestic community, whereas that of the US is more global. [ABSTRACT FROM AUTHOR]

ABSTRACT There have been many studies on the factors influencing paper citation counts. A number of studies have focused on the citing papers, and corresponding methods were proposed to measure the prestige of citations based on the journal impact factors, the total citation counts and the PageRank algorithm values. However, there are drawbacks to these methods. In this paper, we propose a novel method to identify prestigious citations from the affiliation of the citing paper. Specifically, if the authors of the citing paper are affiliated with a prestigious university, the citing paper could be counted as a prestigious citation. As a pilot, we used the top 200 universities on the QS World University Rankings 2015 to identify the prestigious universities so that the prestigious citations, named as QS citations, were identified accordingly. Experimental results validated that QS citations have more important impact on the cited papers than other citations. Papers with QS citations have better performance across most disciplines not only in total citation counts, but also in altmetrics such as the Altmetric Attension Score and Mendeley reader counts. [ABSTRACT FROM AUTHOR]

It has always been argued that social sciences and humanities (SSH) impact evaluation calls for a broader range of indicators than only bibliometric indicators. This study analyzes the performance of scientific SSH publications using 1,327,924 records from the Social Sciences Citation Index (SSCI) and the Arts & Humanities Citation Index (A&HCI), and 629,586 records from Altmetric.com. The research covers a period of 5 years (2013–2017); three publication types (articles, reviews, and proceedings papers); four selected subject fields; three citation indicators; and 13 altmetric indicators. The comparative analysis of SSH performance is studied in both citation and altmetric pattern, and an attempt is made to interpret the results in both the metric and discipline contexts. Major contributions of this study include the extension of analysis methods for the SSH, as well as the validation of altmetric indicators. [ABSTRACT FROM AUTHOR]

In prior work, we proposed a family of metrics as a tool to quantify adherence to or deviation from good citation practices in scholarly research and publishing. We called this family of metrics FAIR as an acronym for Fair Attribution to Indexed Reports and Fair Acknowledgment of Information Records, and introduced definitions for these metrics with counts of instances of correct or incorrect attribution or nonattribution in primary research articles with citations for previously published references. In the present work, we extend our FAIR family of metrics by introducing a collection of ratio‐based metrics to accompany the count‐based metrics described previously. We illustrate the mathematical properties of the ratio‐based metrics with various simulated examples in order to assess their suitability as a means of identifying papers under peer review as more or less likely to be suspicious for plagiarism. These FAIR metrics would alert peer reviewers to prioritize low‐scoring manuscripts for closer scrutiny. Finally, we outline our planned strategy for future validation of the FAIR metrics with an approach using both expert human analysts and automated algorithms for computerized analysis. [ABSTRACT FROM AUTHOR]

With the rapid explosion of information and the dramatic development of bibliometric techniques in the past decades, it becomes a challenge to comprehensively, extensively, and efficiently understand science maps. Aim‐ing to explore in‐depth insights from science maps and predict the dynamics of scientific activities, this paper, based on the co‐occurrence statistics of terms derived from scientific documents, proposes a diffusion‐based network analytic methodology to conduct the prediction study from two aspects: the research interest of scien‐tific researchers and the evolutionary directions of scientific topics. A case study on academic articles down‐loaded from three leading journals in the field of bibliometrics demonstrates the feasibility of the methodology. The future directions of bibliometrics are identified, such as the application of information technologies to tradi‐tional bibliometric data, the interactions between bibliometrics and science, technology, and innovation policy issues, and individual‐level bibliometrics. The results also provide recommendations as potential research inter‐ests for a set of experts. The proposed method could be a toolkit to conduct forecasting studies for a given technological area or a given discipline, and a recommender system to assist academic researchers in identify‐ing potential research interests and extended areas. [ABSTRACT FROM AUTHOR]

Semantic Web and Linked Data promise to change the way we identify, classify, share, find and reuse information by managing and interlinking data so that it can be understood by machines. The benefits identified by the World Wide Web Consortium and other Semantic Web advocates have lead information professionals to explore these possibilities by implementing several initiatives based on Semantic Web technologies in recent years. Just like information science, Semantic Web research is multidisciplinary in nature and can be applied in many different disciplines. In this article, we provide a portrait of research on the Semantic Web using bibliometric methods and investigate the specific contribution of information science literature on the topic. We analyzed 6,438 articles published from 2001 to 2016 retrieved from the Web of Science database to evaluate the evolution of the papers published by discipline and the way the topic was discussed by different discipline. A citation analysis is also conducted. [ABSTRACT FROM AUTHOR]

ABSTRACT Google Scholar (GS) is a database that enables researchers to create their scholarly profiles and keeps track of, among others, their citation counts, and h- and i10-index values. GS is now increasingly being used for research evaluation purposes. Although rich in bibliometric data, GS indexes some duplicate publications and citations, and therefore tends to inflate the citation counts to some extent. Based on a small sample of GS profiles of researchers, this paper aims to study the extent by which duplicates change the citation counts and metrics based thereupon. Findings show that duplicates in GS database somewhat inflates the citation metrics. The scale of the problem as well as the effect of dirty data on performance evaluations based on GS citations data need to be studied further using larger samples. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents results of a study that applies a historical bibliometric treatment on the Journal of the Siam Society in the period from 1972 to 1976, aiming to chart a life story of the Journal in such the timeframe. The research approach taken brings together quantitative and qualitative research methods to trace the historical development of a learned publication devoted to the academic studies of Thailand. The bibliometric methods examine the trend and change in the Journal's bibliographic characteristics which are viewed as the intellectual contours of the Journal. Then, these contours are contextualised and interpreted through historical research methods which primarily engage documentary evidence. The findings of the study show that both bibliometric and historical analyses complement each other, suggesting that the research design and methods are workable. Contributions of the study are outlined. [ABSTRACT FROM AUTHOR]

Citation content Analysis is very useful to reveal the nature of citations among scientific papers. However, most of previous studies had been done only from the side of citing papers and ignored the side of cited papers. We proposed a similarity‐based unsupervised citation text identification method and a ranking‐based supervised cited text identification method. Based on the identified citation and cited texts, we performed a fine‐grained citation analysis and found there was a difference in the cited texts between the citing papers in different disciplines. [ABSTRACT FROM AUTHOR]