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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]

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]

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]

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]

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]

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]

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]

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 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]

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]

We carried out a bibliometric study on web activism, given their absence, for the period between 2007 and 2018, using as a source the Cibermov bibliographic database, created by the documentation service linked to the R&D project Cyber‐activism, digital citizenship and new urban movements, funded by the Government of Spain, as a tool for its members. [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]

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]

New terms and theoretical concepts in information literacy have emerged over the last decade, and these have led to revisions in the standards for information literacy. In order to determine whether information literacy research has reflected these trends, we collected SSCI literature for the 2011 to 2020 period related to information literacy in higher education (ILHE) and conducted analysis using bibliographic mapping and content analysis. Our research found that the volume of research on ILHE has increased in the last five years as compared to the five years before that, and that keywords related to literacy (such as "digital literacy" and "multiliteracies") have been getting a great deal of discussion. After the Framework for Information Literacy for Higher Education (FILHE) was announced, curriculum design research based on the Information Literacy Competency Standards for Higher Education (ILCSHE) continued to outnumber that done based on the Framework. [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]

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]

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]

This study investigates how to measure subject relationship based on bibliographic coupling strength. Since the 1960s, researchers use citation analysis methods to discover the relationship between different works and authors. However, how to apply citation‐based methods in measuring the relationships between various subjects remains unknown. We propose a novel method to measure relationships between subjects based on bibliographic coupling strengths. Our dataset is composed of 7,692 articles published in 10 core information science journals from 2008 to 2017. The result shows that our method provides another viewpoint of exploring the development of science. Furthermore, our method can identify the core works in different subjects and help to judge how similar different subjects are. [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]

The number of Open Access (OA) research articles is trending upward. This research aims to understand the correlations between different OA types and the impact of OA research articles evaluated based on the citation numbers. To avoid bias caused by the publication year, we chose to use COVID‐19 studies in different fields to take advantage of this topic's quick turnaround of data. We analyzed the bibliometrics data and citation numbers (excluding self‐citations) of around 42,000 English language articles published in 2020 related to COVID‐19. We evaluated different types of OA categories such as Gold, Bronze, and Hybrid articles separately. Results show that amongst all OA categories, Hybrid/Green and Bronze/Green OA articles had significant citation advantages. Green OA articles returned more citations than articles with the other OA status. Gold OA articles have no citation advantages compared to non‐OA articles. Gold/Green OA articles had the highest self‐citation rates, followed by Non‐OA articles. The results of the study can be used in understanding different OA categories and the reasons for OA choices. Certain strategies can be made accordingly to improve the awareness of OA in different fields and help OA publishers to improve the OA services. [ABSTRACT FROM AUTHOR]

Research published during the last two decades has frequently discussed how Knowledge Management (KM) is important for libraries. However, we do not know the extent to which KM forms a part of Library and Information Science (LIS) research. In this study, we looked for KM articles published in top LIS journals since 2000. We analyzed publication trends, and the distribution of articles by KM‐related terms used, region/country and information‐setting type. We also identified the top‐cited KM articles published in these LIS journals. 672 KM‐related articles (only 3.84%) were found within the 17,491 articles published in these LIS journals. This low percentage shows that while it might seem like LIS people are advocating for KM in libraries and other information settings, we find that despite the synergies, KM is yet to find a broader place within other LIS concerns. [ABSTRACT FROM AUTHOR]

National Institutes of Health (NIH) is the world largest public funder of biomedical research, investing more than $30 billion dollars to achieve its mission to enhance health, lengthen life, and reduce illness and disability. Here, by leveraging individual‐level characteristics and contextual/time‐dependent features of professional scholarly network, we investigate the chance of NIH Mentored K (MK) to NIH R01 grant (independent research grant) or equivalent (R01‐Eq) transition success. The aim of this work is to explore the relationship between investigator productivity (i.e., scholarly publication) and success (e.g, R01‐Eq funding) during MK to R01‐Eq transition using publicly available datasets and applying our machine learning techniques. The preliminary experiment based on PubMed data and NIH awardees database show that the proposed method is promising, and a number of interesting funding success factors can be located by utilizing statistical tools. [ABSTRACT FROM AUTHOR]

Scientific retractions occur for a multitude of reasons. A growing body of research has studied the phenomenon of retraction through systematic analyses of the characteristics of retracted articles and their associated citations. In our study, we focus on the characteristics of articles that cite retracted articles, and the changes in citation dynamics pre‐ and post‐retraction. We leverage descriptive statistics and ego‐network methods to examine 4,871 retracted articles and their citations before and after retraction. Our retracted articles data was obtained from PubMed, Scopus, and Retraction Watch and their citing articles from Scopus. Our findings indicate a stark decrease in post‐retraction citations and that most of these citations came from countries different from the retracted article's country of publication. Citation context analyses of a subset of retracted articles also reveal that post‐retraction citations came from articles with disciplinary and geographical boundaries different from that of the retracted article. [ABSTRACT FROM AUTHOR]

ABSTRACT In response to the lack of clarity concerning both the conceptual boundaries of information behavior (IB) and the interrelationship between IB and multiple related topics, this study attempts to establish an intellectual profile of IB scholarship by examining publications of IB and 13 other related topics. Results show a similar growth pattern of IB publications and authors over past 45 years. Multidimensional scaling analysis (MDA) based on top frequent terms of the 14 topics revealed a configuration of three clusters and one individual entity (information ecology). IB is found to cluster with topics of seek, need, use, practice, and experience. As the very first study investigating the underlying conceptual connection between IB and 13 other related topics, results of the study help to outline the intellectual affinity of various concepts used in IB related research, add further insights into identifying points of convergence and departure as well as scholarship configuration within the realm of information research. [ABSTRACT FROM AUTHOR]

Citation in academic articles is an important expression of knowledge flow between different disciplines. Analysis of citation content of references from different disciplines can help scholars to understand the role of various disciplines in knowledge flow. This study identifies the discipline of references in academic articles, and then explores the distribution pattern, including cited frequency and cited position (different type of section), of citation content of these references from different disciplines. Finally, we conclude that distribution patterns of different disciplines are different in knowledge flow. Although most references come from natural science, the humanities and social sciences still play an important role in the introduction and background. Basic disciplines like Mathematics are the main providers of methods, and some disciplines relevant to the research topic, like Nursing and Medicine in PLOS, provide more support for the results part of articles. [ABSTRACT FROM AUTHOR]

The availability of large scholarly full‐text datasets with in‐text citations annotated opens the opportunity to investigate how articles have been cited in scientific literature at scale. However, duplicate documents may exist in a dataset, and these duplicates may impact downstream analysis such as calculating citation counts. Document conflation is the task of identifying documents that are nearly identical to each other. This study evaluates document conflation in the Semantic Scholar Open Research Corpus (S2ORC), a dataset containing over 12 million scholarly articles. The evaluation was based on 6,099,232 full‐text S2ORC documents with PubMed IDs (PMIDs) or PubMed Central IDs (PMCIDs). Our findings showed that a portion of S2ORC might contain duplicates. Of the 6,099,232 full‐text documents, 1,280,196 (20.99%) had the same PMIDs or PMCIDs as at least one other document. Pairwise comparisons of their full text found that at least 9.44% of the documents in S2ORC had duplicates. [ABSTRACT FROM AUTHOR]

ABSTRACT Serendipitous discovery has been a research topic for more than one hundred years, but only recently has it been the focus of attention in library and information science (LIS). In 1960, Bernier published the first article on serendipity in a LIS journal. The number of publications gradually grew until 1990s, after which the field experienced a significant interest by the LIS researchers. Currently, LIS researchers are studying serendipity and information encountering from different perspectives, ranging from analyzing various conceptual frameworks to conducting bibliometric studies and investigating factors that trigger and affect the phenomenon. The panel of experts will discuss the issues and challenges of conducting research in this new field of study in LIS. [ABSTRACT FROM AUTHOR]

ABSTRACT This panel brings together experts in bibliometrics and information retrieval to discuss how each of these two important areas of information science can help to inform the research of the other. There is a growing body of literature that capitalizes on the synergies created by combining methodological approaches of each to solve research problems and practical issues related to how information is created, stored, organized, retrieved and used. The session will begin with an overview of the common threads that exist between IR and metrics, followed by a summary of findings from the BIR workshops and examples of research projects that combine aspects of each area to benefit IR or metrics research areas, including search results ranking, semantic indexing and visualization. The panel will conclude with an engaging discussion with the audience to identify future areas of research and collaboration. [ABSTRACT FROM AUTHOR]

Discovering authoritative links between publications and the datasets that they use can be a labor‐intensive process. We introduce a natural language processing pipeline that retrieves and reviews publications for informal references to research datasets, which complements the work of data librarians. We first describe the components of the pipeline and then apply it to expand an authoritative bibliography linking thousands of social science studies to the data‐related publications in which they are used. The pipeline increases recall for literature to review for inclusion in data‐related collections of publications and makes it possible to detect informal data references at scale. We contribute (1) a novel Named Entity Recognition (NER) model that reliably detects informal data references and (2) a dataset connecting items from social science literature with datasets they reference. Together, these contributions enable future work on data reference, data citation networks, and data reuse. [ABSTRACT FROM AUTHOR]

This study uncovered the gap between scientific and technological contributions and scientific and technological influence by tracking scientists who received two national awards that recognized their scientific and technological achievements. The results show that scientific and technological contributions can be made by the same intellectual ideas, indicating the complex relationship between science and technology. Only a few scientists had received a remarkable number of citations of their scientific publications and patents over decades. The contribution–influence gap indicates that quantifying the scientific and technological contributions of some scientists is difficult. [ABSTRACT FROM AUTHOR]

Systematic reviews answer specific questions based on primary literature. However, systematic reviews on the same topic frequently disagree, yet there are no approaches for understanding why at a glance. Our goal is to provide a visual summary that could be useful to researchers, policy makers, and health care professionals in understanding why health controversies persist in the expert literature over time. We present a case study of a single controversy in public health, around the question: "Is reducing dietary salt beneficial at a population level?" We define and visualize three new constructs: the overall evidence base, which consists of the evidence summarized by systematic reviews (the inclusion network) and the unused evidence (isolated nodes). Our network visualization shows at a glance what evidence has been synthesized by each systematic review. Visualizing the temporal evolution of the network captures two key moments when new scientific opinions emerged, both associated with a turn to new sets of evidence that had little to no overlap with previously reviewed evidence. Limited overlap between the evidence reviewed was also found for systematic reviews published in the same year. Future work will focus on understanding the reasons for limited overlap and automating this methodology for medical literature databases. [ABSTRACT FROM AUTHOR]

In this study, we analyzed two decades of the proceedings of the Association for Information Science & Technology (ASIS&T) to uncover bibliometric patterns. We found 3,129 publications from 2000–2020, with more than three‐quarters jointly authored. Most authors are from U.S., Canada, and China. Social media and information behavior are the top‐researched areas. The top‐cited journals are the Journal of the Association for Information Science & Technology, Information Processing and Management, and Library and Information Science Research. The findings affirm ASIS&T's move to an international association and point to the growing importance of collaborative work and social media. The study fills the gap in the analysis of ASIS&T conference proceedings and will help information professionals understand patterns in recent research. This should help guide them in their future research directions. [ABSTRACT FROM AUTHOR]

This panel will present views and critical reflections on peer review, bibliometrics and altmetrics against the background of the latest developments and critique of the scientific system (e.g., replication crisis, DORA, open science, data manipulation). Peer review is the oldest form of monitoring the scientific process and research outcomes and is sometimes considered as the gold standard for evaluating quality. However, it also has its drawbacks; therefore, new forms of peer review are being explored. Bibliometrics, comparative statistics based on publication and citation counts, was introduced as a more objective evaluation method, which is applicable on meso and macro levels of research producing units but is not without problems either. Citation counts as a proxy of quality; the impact factor and the h‐index are some of the most controversial subjects of research evaluation today. The newest addition to the evaluation toolbox are altmetrics, impact measures based mainly on social media activity. Altmetrics have pros and cons as well. None of the measuring devices is perfect, and rather than replacing they complement each other. By drawing on indicators from all three aspects of research evaluation, negative and adverse effects are limited. [ABSTRACT FROM AUTHOR]

How to differentiate citations is continuously an important research question of citation analysis. Recently, some researchers analyze full‐text academic articles with tools and techniques of natural language processing to find out the characteristics of in‐text citations. In this study, we analyze 4,255 articles published during 2007 to 2016 to explore how authors of library and information science (LIS) cite references in their articles. The pattern of citations shows that LIS authors cite more works on average but the average in‐text citation times per reference in an article only increase slightly in this period. There are more in‐text citations in the first quarter fraction of an article and the number of in‐text citations decrease gradually with text progression. The distribution of POS shows that when LIS authors mention references in text body, they use more noun, verb, and preposition than less adjective and adverb. We also choose the high frequency words of different POS to investigate which words authors prefer in in‐text citations. In these high frequency words, nouns tend to be about research topics. Verbs are neutral or used to describe methods or findings of these cited works. As to adjective and adverb, most of them are positive or neutral. But there are more negative words in adverb. [ABSTRACT FROM AUTHOR]

ABSTRACT Co-citation analysis has been widely adopted to represent the intellectual structure of a discipline. In general, all co-cited author pairs are regarded equal. With the development of computer technology and easy accessibility of machine readable full-text articles, new weighting schemes for measuring co-citation strength (CCS) have been proposed. However, in previous studies, only distance and sentence similarity are used to adjust CCS when applying co-citation analysis. In this study, we propose a new approach to measuring CCS based on paragraph similarity. Investigation was carried out to compare our approach and traditional author co-citation analysis (TACA), as well as other different parametric ACAs. Preliminary results show that TACA and distance-based ACA (DACA) share many commonalities. In contrast, similarity-based ACAs reveal the different structure from that of TACA and DACA. However, differences in resulting network structure were still found between paragraph-similarity-based ACA (PACA) and sentence-similarity-based ACA (SACA). Compared to SACA, PACA produces less number of factors and clusters and moderate size of clusters. [ABSTRACT FROM AUTHOR]

ABSTRACT Metrics have become objective standards for evaluating research performance. Measurements such as citation counts and h-index are used for evaluating individual research performance as well as the ranking of research institutions and universities. This exploratory study aims to understand the implications of the increasing use of metrics on scholarly communication and practices. A pilot study was conducted in universities in Ireland. Preliminary findings show that researchers use Google Scholar and ResearchGate for self-monitoring and that they perceive bibliometric measures as indicators of achievements. The pilot study also shows that there are mixed feelings toward bibliometrics: while the participants emphasise that research interest is the most important criterion in choosing research topics and publication channels and that citation counts, h-index, and RG scores are coincidental of their research activities, they also perceive the quantitative measures as objective evaluation of research performance without knowing how the h-index or RG scores are calculated. [ABSTRACT FROM AUTHOR]

Academics are increasingly being asked to demonstrate the impact of their research beyond the walls of the academy. Societal impact measures were introduced as part of the Research Excellence Framework exercise in the UK in 2014 with a number of other countries, including Australia, considering similar assessments. As societal impact measures continue to proliferate there will be significant implications for academics, institutions, and academic libraries to document and support these activities. Information science is well-placed not only to guide practical supports within our institutions, but also to develop metrics and qualitative approaches to assess this type of research impact. This exploratory qualitative study -- situated in a constructivist grounded theory methodology -- investigated academics' experiences and perceptions of the concept of societal research impact and the supports needed to facilitate this work. The definition of impact varied greatly among participants, but regardless of the participant's conception, interviewees felt that they were not prepared, trained, or had access to the needed supports to adequately document non-academic types of impact. The data point to a number of emergent themes including a lack of relevant methodologies for tracking societal impact, the shortcomings of metrics approaches to document impact outside of academe, and the need for academic libraries to extend current reference and training supports to provide researchers with the tools and skills needed in this new impact landscape. Implications for research and development in information science related to scholarly communication, researchers' information behaviors, and impact measures are also explored. [ABSTRACT FROM AUTHOR]

Building upon well-established paradigms brought forth by such theorists as Robert K. Merton, Pierre Bourdieu, and Blaise Cronin, the panel will span the full cycle of academic production to show, through various bibliometric measures and other quantitative and qualitative analyses, how the reward system of science is evolving. While there is strong evidence to suggest that such forms of dissemination as social media output and blogging are being incorporated into scientific practices, scientific impact still remains principally assessed using measures such as authorship and citations, whilst other elements, such as acknowledgements, have received varying levels of regard at various times. Disciplinary considerations also arise. Using a wide range of approaches, measures, and datasets, the panelists will establish links between their individual research to create an empirically driven picture of the reward system of science and its indicators. Through the use of the Polldaddy application, audience members will answer questions and create an overview of their perception of the reward system of science. [ABSTRACT FROM AUTHOR]

This study proposes a weighted random walk method on co-word networks to identify important themes of a field using structural features of the networks. The goal is to test whether the weighted random walk method can be used to produce meaningful results on co-word networks. In addition, we examined the relationships among the results from the random walk method and other two common metrics for identifying important themes in a field: frequency and point centrality. Using a dataset of 17K bibliographic records for the articles in the LIS field from the Web of Science, our results indicate that all three measures are significantly correlated. A detailed comparison of the top terms ranked by the three metrics from the years of 2002-2006 and 2007- 2012 is provided. The results show that the three measures are generally similar in revealing hotspots and development of the field. However, some noticeable differences are also found. The random walk method boosted the rankings of some lower ranked terms in the other two metrics (e.g. "universe", "servic" and "develop") due to their cooccurrences with top ranked terms (e.g. "information"). The findings of this study help to understand the use of random walk method on co-word networks. [ABSTRACT FROM AUTHOR]

ABSTRACT This study examines the open access citation advantage of gold open access (OA) journal articles published at a large U.S. research university. Most studies that examine the open access citation advantage focus on specific journals, disciplines, countries or global output. Local citation patterns may differ from these larger patterns. Since many OA advocates mention the open access citation advantage when promoting OA journal publishing on university campuses, an understanding of local patterns is crucial. This study reports on a method and compares average citation counts for subscription and gold OA journal articles using Web of Science. Gold OA physics journals showed a definite open access citation advantage, whereas other disciplines showed no difference or no open access citation advantage. [ABSTRACT FROM AUTHOR]