Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive mo...Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive more specific information about the kind of received impact.Design/methodology/approach:Bornmann,Wray,and Haunschild(2019)introduced citation concept analysis(CCA)for capturing the importance and usefulness certain concepts have in subsequent research.The method is based on the analysis of citances-the contexts of citations in citing papers.This study applies the method by investigating the impact of various concepts introduced in the oeuvre of the world-leading French sociologist Pierre Bourdieu.Findings:We found that the most cited concepts are‘social capital’(with about 34%of the citances in the citing papers),‘cultural capital’,and‘habitus’(both with about 24%).On the other hand,the concepts‘doxa’and‘reflexivity’score only about 1%each.Research limitations:The formulation of search terms for identifying the concepts in the data and the citation context coverage are the most important limitations of the study.Practical implications:The results of this explorative study reflect the historical development of Bourdieu’s thought and its interface with different fields of study.Originality/value:The study demonstrates the high explanatory power of the CCA method.展开更多
Purpose:This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics,focusing on the interplay between journal publication growth and citation dynamics.Desig...Purpose:This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics,focusing on the interplay between journal publication growth and citation dynamics.Design/methodology/approach:We analyze bibliometric data from three prominent fluids journals-Physics of Fluids,Journal of Fluid Mechanics,and Physical Review Fluids-over the period 1999-2023.The analysis examines the relations among annual fractional journal publication growth,citation growth,and bibliographic metric suppressions.Findings:Our findings reveal that the suppression of impact factor growth is significantly influenced by annual fractional journal publication growth rather than citation growth.All three journals exhibit similar responses to publication growth with minimal scatter,following a consistent functional relation.We also identify narrow,nearly Gaussian distributions for annual fractional journal publication growth.Furthermore,we introduce a new growth-independent dimensionless bibliometric metric,journal urgency,the ratio of annual fractional citation growth to the 4-year running average immediacy index.This metric captures effectively the dependency of citation growth on urgency and reveals consistent distributions across the journals analyzed.Research limitations:The study is limited to three major fluids journals and to the availability of bibliometric data from 1999 to 2023.Future work could extend the analysis to other disciplines and journals.Practical implications:Understanding the relation between publication growth and bibliometric suppressions can inform editorial and strategic decisions in journal management.The proposed journal urgency metric offers a novel tool for assessing and comparing journal performance independent of growth rates.Originality/value:This study introduces a new bibliometric metric-journal urgency-that provides fresh insights into citation dynamics and bibliographic metric behavior.It highlights the critical role of publication growth in shaping journal impact factors and CiteScores,offering a unified framework applicable across multiple journals.展开更多
Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)...Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.展开更多
A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than tw...A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than two thousand of A-shares from 2017 to 2020 were selected.The effect of the traditional patent forward citation and the price-citation for discriminating the stock return rate was thoroughly analyzed via ANOVA.The A-shares of forward citation counts above the average showed higher stock return rate means than the A-shares having patents but receiving no forward citations.The price-citation,combining both the financial and patent attributes,defined as the multiplication of the current stock price and the currently receiving forward citation count,showed its excellence in discriminating the stock return rate.The A-shares of higher price-citation showed significantly higher stock return rate means while the A-shares of lower price-citation showed significantly lowest stock return rate means.The price-citation effect had not been changed by COVID-19 though COVID-19 affected the social and economic environment to a considerable extent in 2020.展开更多
Purpose:The goal of this study is a comparative analysis of the relation between funding(a main driver for scientific research)and citations in papers of Nobel Laureates in physics,chemistry and medicine over 2019-202...Purpose:The goal of this study is a comparative analysis of the relation between funding(a main driver for scientific research)and citations in papers of Nobel Laureates in physics,chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.Design/methodology/approach:This study utilizes a power law model to explore the relationship between research funding and citations of related papers.The study here analyzes 3,539 recorded documents by Nobel Laureates in physics,chemistry and medicine and a broader dataset of 183,016 documents related to the fields of physics,medicine,and chemistry recorded in the Web of Science database.Findings:Results reveal that in chemistry and medicine,funded researches published in papers of Nobel Laureates have higher citations than unfunded studies published in articles;vice versa high citations of Nobel Laureates in physics are for unfunded studies published in papers.Instead,when overall data of publications and citations in physics,chemistry and medicine are analyzed,all papers based on funded researches show higher citations than unfunded ones.Originality/value:Results clarify the driving role of research funding for science diffusion that are systematized in general properties:a)articles concerning funded researches receive more citations than(un)funded studies published in papers of physics,chemistry and medicine sciences,generating a high Matthew effect(a higher growth of citations with the increase in the number of papers);b)research funding increases the citations of articles in fields oriented to applied research(e.g.,chemistry and medicine)more than fields oriented towards basic research(e.g.,physics).Practical implications:The results here explain some characteristics of scientific development and diffusion,highlighting the critical role of research funding in fostering citations and the expansion of scientific knowledge.This finding can support decision-making of policymakers and R&D managers to improve the effectiveness in allocating financial resources in science policies to generate a higher positive scientific and societal impact.展开更多
Purpose： （1） To test basic assumptions underlying frequency-weighted citation analysis： （a） Uni-citations correspond to citations that are nonessential to the citing papers; （b） The influence of a cited paper ...Purpose： （1） To test basic assumptions underlying frequency-weighted citation analysis： （a） Uni-citations correspond to citations that are nonessential to the citing papers; （b） The influence of a cited paper on the citing paper increases with the frequency with which it is cited in the citing paper. （2） To explore the degree to which citation location may be used to help identify nonessential citations. Design/methodology/approach： Each of the in-text citations in all research articles published in Issue 1 of the Journal of the Association for Information Science and Technology （JASIST） 2016 was manually classified into one of these five categories： Applied, Contrastive, Supportive, Reviewed, and Perfunctory. The distributions of citations at different in-text frequencies and in different locations in the text by these functions were analyzed. Findings： Filtering out nonessential citations before assigning weight is important for frequency-weighted citation analysis. For this purpose, removing citations by location is more effective than re-citation analysis that simply removes uni-citations. Removing all citation occurrences in the Background and Literature Review sections and uni-citations in the Introduction section appears to provide a good balance between filtration and error rates. Research limitations： This case study suffers from the limitation of scalability and generalizability. We took careful measures to reduce the impact of other limitations of the data collection approach used. Relying on the researcher＇s judgment to attribute citation functions, this approach is unobtrusive but speculative, and can suffer from a low degree of confidence, thus creating reliability concerns. Practical implications： Weighted citation analysis promises to improve citation analysis for research evaluation, knowledge network analysis, knowledge representation, and information retrieval. The present study showed the importance of filtering out nonessential citations before assigning weight in a weighted citation analysis, which may be a significant step forward to realizing these promises. Originality/value： Weighted citation analysis has long been proposed as a theoretical solution to the problem of citation analysis that treats all citations equally, and has attracted increasing research interest in recent years. The present study showed, for the first time, the importance of filtering out nonessential citations in weighted citation analysis, pointing research in this area in a new direction.展开更多
Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relati...Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database.Findings:The original results reveal general characteristics of the diffusion of science in research fields:a)Funded articles receive higher citations compared to unfunded papers in journals;b)Funded articles exhibit a super-linear growth in citations,surpassing the increase seen in unfunded articles.This finding reveals a higher diffusion of scientific knowledge in funded articles.Moreover,c)funded articles in both basic and applied sciences demonstrate a similar expected change in citations,equivalent to about 1.23%,when the number of funded papers increases by 1%in journals.This result suggests,for the first time,that funding effect of scientific research is an invariant driver,irrespective of the nature of the basic or applied sciences.Originality/value:This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society.These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences.Practical implications:This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society.展开更多
In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniq...In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.展开更多
Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at t...Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at the micro,meso,and macro levels of analysis.Design/methodology/approach:We used bibliometric network analysis,including the“temporal quantities”approach proposed to study temporal networks.Using a two-mode network linking publications with authors and a one-mode network of citations between the works,we constructed and analyzed the networks of citation and bibliographic coupling among authors.We used an iterated saturation data collection approach.Findings:At the macro-level,we observed the global structural features of citations between authors,showing that 80%of authors have not more than 15 citations from other works.At the meso-level,we extracted the groups of authors citing each other and similar to each other according to their citation patterns.We have seen a division of authors in SNA into groups of social scientists and physicists,as well as into other groups of authors from different disciplines.We found some examples of brokerage between different groups that maintained the common identity of the field.At the micro-level,we extracted authors with extremely high values of received citations,who can be considered as the most prominent authors in the field.We examined the temporal properties of the most popular authors.Research limitations:The main challenge in this approach is the resolution of the author’s name(synonyms and homonyms).We faced the author disambiguation,or“multiple personalities”(Harzing,2015)problem.To remain consistent and comparable with our previously published articles,we used the same SNA data collected up to 2018.The analysis and conclusions on the activity,productivity,and visibility of the authors are relative only to the field of SNA.Practical implications:The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines.This may potentially inspire the application of network approaches in other research areas,creating more authors collaborating in the field of SNA.Originality/value:We identified and applied an innovative approach and methods to study the structure of scientific communities,which allowed us to get the findings going beyond those obtained with other methods.We used a new approach to temporal network analysis,which is an important addition to the analysis as it provides detailed information on different measures for the authors and pairs of authors over time.展开更多
Purpose:To analyze the diversity of citation distributions to publications in different research topics to investigate the accuracy of size-independent,rank-based indicators.The top percentile-based indicators are the...Purpose:To analyze the diversity of citation distributions to publications in different research topics to investigate the accuracy of size-independent,rank-based indicators.The top percentile-based indicators are the most common indicators of this type,and the evaluations of Japan are the most evident misjudgments.Design/methodology/approach:The distributions of citations to publications from countries and journals in several research topics were analyzed along with the corresponding global publications using histograms with logarithmic binning,double rank plots,and normal probability plots of log-transformed numbers of citations.Findings:Size-independent,top percentile-based indicators are accurate when the global ranks of local publications fit a power law,but deviations in the least cited papers are frequent in countries and occur in all journals with high impact factors.In these cases,a single indicator is misleading.Comparisons of the proportions of uncited papers are the best way to predict these deviations.Research limitations:This study is fundamentally analytical,and its results describe mathematical facts that are self-evident.Practical implications:Respectable institutions,such as the OECD,the European Commission,and the U.S.National Science Board,produce research country rankings and individual evaluations using size-independent percentile indicators that are misleading in many countries.These misleading evaluations should be discontinued because they can cause confusion among research policymakers and lead to incorrect research policies.Originality/value:Studies linking the lower tail of citation distribution,including uncited papers,to percentile research indicators have not been performed previously.The present results demonstrate that studies of this type are necessary to find reliable procedures for research assessments.展开更多
Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy o...Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.展开更多
Background:This study aimed to conduct a bibliometric analysis of positive mental health,focusing on citation performance,article title,abstract,author keywords,Keyword Plus,and their development trends.The novelty of...Background:This study aimed to conduct a bibliometric analysis of positive mental health,focusing on citation performance,article title,abstract,author keywords,Keyword Plus,and their development trends.The novelty of this study is a pioneer within the field of positive mental health.Therefore,it delivered new ideas for researchers and practitioners who had concerns about positive mental health in terms of trends research which covered recommended articles and the research focus in recent years.Methods:The data were retrieved on 30 April 2024 from the Social Sciences Citation Index(SSCI)of Clarivate Analytics’Web of Science Core Collection for studies published between 1992 and 2023.Results:The distribution of keywords in the article title and keywords chosen by the authors were used to assess research trends.1391 documents in SSCI were found during the search;1221 of these were document-type“articles.”524 journals published these publications.The most frequently used keywords by the writers,according to the articles’analysis,are“depression,”“resilience,”“COVID-19,”“anxiety,”and“social support.”Kristin D.Neff wrote the most frequently cited paper in 2003.Most articles came from Europe(five countries),America(two countries),Asia(two countries),and Oceania(one country),and were published in English.The majority of the research in the field of positive mental health is conducted in Europe and America,two regions where English is the primary language.The main research topics in positive mental health were related to adolescents,children,and college students.Conclusion:Trends research through bibliometric analysis by using data from Web of Science Core Collection should be followed by manual inspection to avoid errors.Therefore,scientists need more careful data examination in bibliometric analysis.展开更多
Purpose:Researchers frequently encounter the following problems when writing scientific articles:(1)Selecting appropriate citations to support the research idea is challenging.(2)The literature review is not conducted...Purpose:Researchers frequently encounter the following problems when writing scientific articles:(1)Selecting appropriate citations to support the research idea is challenging.(2)The literature review is not conducted extensively,which leads to working on a research problem that others have well addressed.The study focuses on citation recommendation in the related studies section by applying the term function of a citation context,potentially improving the efficiency of writing a literature review.Design/methodology/approach:We present nine term functions with three newly created and six identified from existing literature.Using these term functions as labels,we annotate 531 research papers in three topics to evaluate our proposed recommendation strategy.BM25 and Word2vec with VSM are implemented as the baseline models for the recommendation.Then the term function information is applied to enhance the performance.Findings:The experiments show that the term function-based methods outperform the baseline methods regarding the recall,precision,and F1-score measurement,demonstrating that term functions are useful in identifying valuable citations.Research limitations:The dataset is insufficient due to the complexity of annotating citation functions for paragraphs in the related studies section.More recent deep learning models should be performed to future validate the proposed approach.Practical implications:The citation recommendation strategy can be helpful for valuable citation discovery,semantic scientific retrieval,and automatic literature review generation.Originality/value:The proposed citation function-based citation recommendation can generate intuitive explanations of the results for users,improving the transparency,persuasiveness,and effectiveness of recommender systems.展开更多
Purpose:We study the proportion of Web of Science(WoS)citation links that are represented in the Crossref Open Citation Index(COCI),with the possible aim of using COCI in research evaluation instead of the WoS,if the ...Purpose:We study the proportion of Web of Science(WoS)citation links that are represented in the Crossref Open Citation Index(COCI),with the possible aim of using COCI in research evaluation instead of the WoS,if the level of coverage was sufficient.Design/methodology/approach:We calculate the proportion on citation links where both publications have a WoS accession number and a DOI simultaneously,and where the cited publications have had at least one author from our institution,the Czech Technical University in Prague.We attempt to look up each such citation link in COCI.Findings:We find that 53.7%of WoS citation links are present in the COCI.The proportion varies largely by discipline.The total figures differ significantly from 40%in the large-scale study by Van Eck,Waltman,Larivière,and Sugimoto(blog 2018,https://www.cwts.nl/blog?article=n-r2s234).Research limitations:The sample does not cover all science areas uniformly;it is heavily focused on Engineering and Technology,and only some disciplines of Natural Sciences are present.However,this reflects the real scientific orientation and publication profile of our institution.Practical implications:The current level of coverage is not sufficient for the WoS to be replaced by COCI for research evaluation.Originality/value:The present study illustrates a COCI vs WoS comparison on the scale of a larger technical university in Central Europe.展开更多
Purpose:Providing an overview of types of citation curves.Design/methodology/approach:The terms citation curves or citation graphs are made explicit.Findings:A framework for the study of diachronous(and synchronous)ci...Purpose:Providing an overview of types of citation curves.Design/methodology/approach:The terms citation curves or citation graphs are made explicit.Findings:A framework for the study of diachronous(and synchronous)citation curves is proposed.Research limitations:No new practical applications are given.Practical implications:This short note about citation curves will help readers to make the optimal choice for their applications.Originality/value:A new scheme for the meaning of the term"citation curve"is designed.展开更多
Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals,researchers,institutions,and countries.Authors cite papers for different reasons...Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals,researchers,institutions,and countries.Authors cite papers for different reasons,such as extending previous work,comparing their study with the state-of-the-art,providing background of the field,etc.In recent years,researchers have tried to conceptualize all citations into two broad categories,important and incidental.Such a categorization is very important to enhance scientific output in multiple ways,for instance,(1)Helping a researcher in identifying meaningful citations from a list of 100 to 1000 citations(2)Enhancing the impact factor calculation mechanism by more strongly weighting important citations,and(3)Improving researcher,institutional,and university rankings by only considering important citations.All of these uses depend upon correctly identifying the important citations from the list of all citations in a paper.To date,researchers have utilized many features to classify citations into these broad categories:cue phrases,in-text citation counts,and metadata features,etc.However,contemporary approaches are based on identification of in-text citation counts,mapping sections onto the Introduction,Methods,Results,and Discussion(IMRAD)structure,identifying cue phrases,etc.Identifying such features accurately is a challenging task and is normally conducted manually,with the accuracy of citation classification demonstrated in terms of these manually extracted features.This research proposes to examine the content of the cited and citing pair to identify important citing papers for each cited paper.This content similarity approach was adopted from research paper recommendation approaches.Furthermore,a novel section-based content similarity approach is also proposed.The results show that solely using the abstract of the cited and citing papers can achieve similar accuracy as the stateof-the-art approaches.This makes the proposed approach a viable technique that does not depend on manual identification of complex features.展开更多
Citations based relevant research paper recommendations can be generated primarily with the assistance of three citation models:(1)Bibliographic Coupling,(2)Co-Citation,and(3)Direct Citations.Millions of new scholarly...Citations based relevant research paper recommendations can be generated primarily with the assistance of three citation models:(1)Bibliographic Coupling,(2)Co-Citation,and(3)Direct Citations.Millions of new scholarly articles are published every year.This flux of scientific information has made it a challenging task to devise techniques that could help researchers to find the most relevant research papers for the paper at hand.In this study,we have deployed an in-text citation analysis that extends the Direct Citation Model to discover the nature of the relationship degree-ofrelevancy among scientific papers.For this purpose,the relationship between citing and cited articles is categorized into three categories:weak,medium,and strong.As an experiment,around 5,000 research papers were crawled from the CiteSeerX.These research papers were parsed for the identification of in-text citation frequencies.Subsequently,0.1 million references of those articles were extracted,and their in-text citation frequencies were computed.A comprehensive benchmark dataset was established based on the user study.Afterwards,the results were validated with the help of Least Square Approximation by Quadratic Polynomial method.It was found that degreeof-relevancy between scientific papers is a quadratic increasing/decreasing polynomial with respect to-increase/decrease in the in-text citation frequencies of a cited article.Furthermore,the results of the proposed model were compared with state-of-the-art techniques by utilizing a well-known measure,known as the normalized Discount Cumulative Gain(nDCG).The proposed method received an nDCG score of 0.89,whereas the state-of-the-art models such as the Content,Bibliographic-coupling,and Metadata-based Models were able to acquire the nDCG values of 0.65,0.54,and 0.51 respectively.These results indicate that the proposed mechanism may be applied in future information retrieval systems for better results.展开更多
Recent time handling uncertainty and its measurement is considered as one of the major issues by data science and applied mathematics researchers. It becomes more complex when the dynamicity exists in data sets. One o...Recent time handling uncertainty and its measurement is considered as one of the major issues by data science and applied mathematics researchers. It becomes more complex when the dynamicity exists in data sets. One of the suitable examples is Scopus data sets which changes every time. In this case, precise measurement of consistency in document and citation publications is considered as one of the issues. It becomes more complex when the parameter like h-index and document count can be also manipulated over the period of time. To resolve this issue, a time-based index called as “t-index” is illustrated in this paper with an example. This method measures the randomness in document publication and citation using the average h-index and its entropy measurement.展开更多
文摘Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive more specific information about the kind of received impact.Design/methodology/approach:Bornmann,Wray,and Haunschild(2019)introduced citation concept analysis(CCA)for capturing the importance and usefulness certain concepts have in subsequent research.The method is based on the analysis of citances-the contexts of citations in citing papers.This study applies the method by investigating the impact of various concepts introduced in the oeuvre of the world-leading French sociologist Pierre Bourdieu.Findings:We found that the most cited concepts are‘social capital’(with about 34%of the citances in the citing papers),‘cultural capital’,and‘habitus’(both with about 24%).On the other hand,the concepts‘doxa’and‘reflexivity’score only about 1%each.Research limitations:The formulation of search terms for identifying the concepts in the data and the citation context coverage are the most important limitations of the study.Practical implications:The results of this explorative study reflect the historical development of Bourdieu’s thought and its interface with different fields of study.Originality/value:The study demonstrates the high explanatory power of the CCA method.
文摘Purpose:This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics,focusing on the interplay between journal publication growth and citation dynamics.Design/methodology/approach:We analyze bibliometric data from three prominent fluids journals-Physics of Fluids,Journal of Fluid Mechanics,and Physical Review Fluids-over the period 1999-2023.The analysis examines the relations among annual fractional journal publication growth,citation growth,and bibliographic metric suppressions.Findings:Our findings reveal that the suppression of impact factor growth is significantly influenced by annual fractional journal publication growth rather than citation growth.All three journals exhibit similar responses to publication growth with minimal scatter,following a consistent functional relation.We also identify narrow,nearly Gaussian distributions for annual fractional journal publication growth.Furthermore,we introduce a new growth-independent dimensionless bibliometric metric,journal urgency,the ratio of annual fractional citation growth to the 4-year running average immediacy index.This metric captures effectively the dependency of citation growth on urgency and reveals consistent distributions across the journals analyzed.Research limitations:The study is limited to three major fluids journals and to the availability of bibliometric data from 1999 to 2023.Future work could extend the analysis to other disciplines and journals.Practical implications:Understanding the relation between publication growth and bibliometric suppressions can inform editorial and strategic decisions in journal management.The proposed journal urgency metric offers a novel tool for assessing and comparing journal performance independent of growth rates.Originality/value:This study introduces a new bibliometric metric-journal urgency-that provides fresh insights into citation dynamics and bibliographic metric behavior.It highlights the critical role of publication growth in shaping journal impact factors and CiteScores,offering a unified framework applicable across multiple journals.
文摘Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.
基金support from Ministry of Science and Technology,Taiwan,R.O.C.under Grant No.MOST 109-2410-H-011-021-MY3.
文摘A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than two thousand of A-shares from 2017 to 2020 were selected.The effect of the traditional patent forward citation and the price-citation for discriminating the stock return rate was thoroughly analyzed via ANOVA.The A-shares of forward citation counts above the average showed higher stock return rate means than the A-shares having patents but receiving no forward citations.The price-citation,combining both the financial and patent attributes,defined as the multiplication of the current stock price and the currently receiving forward citation count,showed its excellence in discriminating the stock return rate.The A-shares of higher price-citation showed significantly higher stock return rate means while the A-shares of lower price-citation showed significantly lowest stock return rate means.The price-citation effect had not been changed by COVID-19 though COVID-19 affected the social and economic environment to a considerable extent in 2020.
文摘Purpose:The goal of this study is a comparative analysis of the relation between funding(a main driver for scientific research)and citations in papers of Nobel Laureates in physics,chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.Design/methodology/approach:This study utilizes a power law model to explore the relationship between research funding and citations of related papers.The study here analyzes 3,539 recorded documents by Nobel Laureates in physics,chemistry and medicine and a broader dataset of 183,016 documents related to the fields of physics,medicine,and chemistry recorded in the Web of Science database.Findings:Results reveal that in chemistry and medicine,funded researches published in papers of Nobel Laureates have higher citations than unfunded studies published in articles;vice versa high citations of Nobel Laureates in physics are for unfunded studies published in papers.Instead,when overall data of publications and citations in physics,chemistry and medicine are analyzed,all papers based on funded researches show higher citations than unfunded ones.Originality/value:Results clarify the driving role of research funding for science diffusion that are systematized in general properties:a)articles concerning funded researches receive more citations than(un)funded studies published in papers of physics,chemistry and medicine sciences,generating a high Matthew effect(a higher growth of citations with the increase in the number of papers);b)research funding increases the citations of articles in fields oriented to applied research(e.g.,chemistry and medicine)more than fields oriented towards basic research(e.g.,physics).Practical implications:The results here explain some characteristics of scientific development and diffusion,highlighting the critical role of research funding in fostering citations and the expansion of scientific knowledge.This finding can support decision-making of policymakers and R&D managers to improve the effectiveness in allocating financial resources in science policies to generate a higher positive scientific and societal impact.
文摘Purpose： （1） To test basic assumptions underlying frequency-weighted citation analysis： （a） Uni-citations correspond to citations that are nonessential to the citing papers; （b） The influence of a cited paper on the citing paper increases with the frequency with which it is cited in the citing paper. （2） To explore the degree to which citation location may be used to help identify nonessential citations. Design/methodology/approach： Each of the in-text citations in all research articles published in Issue 1 of the Journal of the Association for Information Science and Technology （JASIST） 2016 was manually classified into one of these five categories： Applied, Contrastive, Supportive, Reviewed, and Perfunctory. The distributions of citations at different in-text frequencies and in different locations in the text by these functions were analyzed. Findings： Filtering out nonessential citations before assigning weight is important for frequency-weighted citation analysis. For this purpose, removing citations by location is more effective than re-citation analysis that simply removes uni-citations. Removing all citation occurrences in the Background and Literature Review sections and uni-citations in the Introduction section appears to provide a good balance between filtration and error rates. Research limitations： This case study suffers from the limitation of scalability and generalizability. We took careful measures to reduce the impact of other limitations of the data collection approach used. Relying on the researcher＇s judgment to attribute citation functions, this approach is unobtrusive but speculative, and can suffer from a low degree of confidence, thus creating reliability concerns. Practical implications： Weighted citation analysis promises to improve citation analysis for research evaluation, knowledge network analysis, knowledge representation, and information retrieval. The present study showed the importance of filtering out nonessential citations before assigning weight in a weighted citation analysis, which may be a significant step forward to realizing these promises. Originality/value： Weighted citation analysis has long been proposed as a theoretical solution to the problem of citation analysis that treats all citations equally, and has attracted increasing research interest in recent years. The present study showed, for the first time, the importance of filtering out nonessential citations in weighted citation analysis, pointing research in this area in a new direction.
文摘Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database.Findings:The original results reveal general characteristics of the diffusion of science in research fields:a)Funded articles receive higher citations compared to unfunded papers in journals;b)Funded articles exhibit a super-linear growth in citations,surpassing the increase seen in unfunded articles.This finding reveals a higher diffusion of scientific knowledge in funded articles.Moreover,c)funded articles in both basic and applied sciences demonstrate a similar expected change in citations,equivalent to about 1.23%,when the number of funded papers increases by 1%in journals.This result suggests,for the first time,that funding effect of scientific research is an invariant driver,irrespective of the nature of the basic or applied sciences.Originality/value:This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society.These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences.Practical implications:This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society.
基金supported by the National Natural Science Foundation of China(No.62271274).
文摘In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.
基金supported in part by the Slovenian Research Agency(VB,research program P1-0294)(VB,research project J5-2557)+2 种基金(VB,research project J5-4596)COST EU(VB,COST action CA21163(HiTEc)is prepared within the framework of the HSE University Basic Research Program.
文摘Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at the micro,meso,and macro levels of analysis.Design/methodology/approach:We used bibliometric network analysis,including the“temporal quantities”approach proposed to study temporal networks.Using a two-mode network linking publications with authors and a one-mode network of citations between the works,we constructed and analyzed the networks of citation and bibliographic coupling among authors.We used an iterated saturation data collection approach.Findings:At the macro-level,we observed the global structural features of citations between authors,showing that 80%of authors have not more than 15 citations from other works.At the meso-level,we extracted the groups of authors citing each other and similar to each other according to their citation patterns.We have seen a division of authors in SNA into groups of social scientists and physicists,as well as into other groups of authors from different disciplines.We found some examples of brokerage between different groups that maintained the common identity of the field.At the micro-level,we extracted authors with extremely high values of received citations,who can be considered as the most prominent authors in the field.We examined the temporal properties of the most popular authors.Research limitations:The main challenge in this approach is the resolution of the author’s name(synonyms and homonyms).We faced the author disambiguation,or“multiple personalities”(Harzing,2015)problem.To remain consistent and comparable with our previously published articles,we used the same SNA data collected up to 2018.The analysis and conclusions on the activity,productivity,and visibility of the authors are relative only to the field of SNA.Practical implications:The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines.This may potentially inspire the application of network approaches in other research areas,creating more authors collaborating in the field of SNA.Originality/value:We identified and applied an innovative approach and methods to study the structure of scientific communities,which allowed us to get the findings going beyond those obtained with other methods.We used a new approach to temporal network analysis,which is an important addition to the analysis as it provides detailed information on different measures for the authors and pairs of authors over time.
文摘Purpose:To analyze the diversity of citation distributions to publications in different research topics to investigate the accuracy of size-independent,rank-based indicators.The top percentile-based indicators are the most common indicators of this type,and the evaluations of Japan are the most evident misjudgments.Design/methodology/approach:The distributions of citations to publications from countries and journals in several research topics were analyzed along with the corresponding global publications using histograms with logarithmic binning,double rank plots,and normal probability plots of log-transformed numbers of citations.Findings:Size-independent,top percentile-based indicators are accurate when the global ranks of local publications fit a power law,but deviations in the least cited papers are frequent in countries and occur in all journals with high impact factors.In these cases,a single indicator is misleading.Comparisons of the proportions of uncited papers are the best way to predict these deviations.Research limitations:This study is fundamentally analytical,and its results describe mathematical facts that are self-evident.Practical implications:Respectable institutions,such as the OECD,the European Commission,and the U.S.National Science Board,produce research country rankings and individual evaluations using size-independent percentile indicators that are misleading in many countries.These misleading evaluations should be discontinued because they can cause confusion among research policymakers and lead to incorrect research policies.Originality/value:Studies linking the lower tail of citation distribution,including uncited papers,to percentile research indicators have not been performed previously.The present results demonstrate that studies of this type are necessary to find reliable procedures for research assessments.
基金supported by the National Natural Science Foundation of China(Grant No.71974167).
文摘Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.
文摘Background:This study aimed to conduct a bibliometric analysis of positive mental health,focusing on citation performance,article title,abstract,author keywords,Keyword Plus,and their development trends.The novelty of this study is a pioneer within the field of positive mental health.Therefore,it delivered new ideas for researchers and practitioners who had concerns about positive mental health in terms of trends research which covered recommended articles and the research focus in recent years.Methods:The data were retrieved on 30 April 2024 from the Social Sciences Citation Index(SSCI)of Clarivate Analytics’Web of Science Core Collection for studies published between 1992 and 2023.Results:The distribution of keywords in the article title and keywords chosen by the authors were used to assess research trends.1391 documents in SSCI were found during the search;1221 of these were document-type“articles.”524 journals published these publications.The most frequently used keywords by the writers,according to the articles’analysis,are“depression,”“resilience,”“COVID-19,”“anxiety,”and“social support.”Kristin D.Neff wrote the most frequently cited paper in 2003.Most articles came from Europe(five countries),America(two countries),Asia(two countries),and Oceania(one country),and were published in English.The majority of the research in the field of positive mental health is conducted in Europe and America,two regions where English is the primary language.The main research topics in positive mental health were related to adolescents,children,and college students.Conclusion:Trends research through bibliometric analysis by using data from Web of Science Core Collection should be followed by manual inspection to avoid errors.Therefore,scientists need more careful data examination in bibliometric analysis.
基金This work is supported by the National Natural Science Foundation of China(Grant No.7167030644 and 71704137)。
文摘Purpose:Researchers frequently encounter the following problems when writing scientific articles:(1)Selecting appropriate citations to support the research idea is challenging.(2)The literature review is not conducted extensively,which leads to working on a research problem that others have well addressed.The study focuses on citation recommendation in the related studies section by applying the term function of a citation context,potentially improving the efficiency of writing a literature review.Design/methodology/approach:We present nine term functions with three newly created and six identified from existing literature.Using these term functions as labels,we annotate 531 research papers in three topics to evaluate our proposed recommendation strategy.BM25 and Word2vec with VSM are implemented as the baseline models for the recommendation.Then the term function information is applied to enhance the performance.Findings:The experiments show that the term function-based methods outperform the baseline methods regarding the recall,precision,and F1-score measurement,demonstrating that term functions are useful in identifying valuable citations.Research limitations:The dataset is insufficient due to the complexity of annotating citation functions for paragraphs in the related studies section.More recent deep learning models should be performed to future validate the proposed approach.Practical implications:The citation recommendation strategy can be helpful for valuable citation discovery,semantic scientific retrieval,and automatic literature review generation.Originality/value:The proposed citation function-based citation recommendation can generate intuitive explanations of the results for users,improving the transparency,persuasiveness,and effectiveness of recommender systems.
文摘Purpose:We study the proportion of Web of Science(WoS)citation links that are represented in the Crossref Open Citation Index(COCI),with the possible aim of using COCI in research evaluation instead of the WoS,if the level of coverage was sufficient.Design/methodology/approach:We calculate the proportion on citation links where both publications have a WoS accession number and a DOI simultaneously,and where the cited publications have had at least one author from our institution,the Czech Technical University in Prague.We attempt to look up each such citation link in COCI.Findings:We find that 53.7%of WoS citation links are present in the COCI.The proportion varies largely by discipline.The total figures differ significantly from 40%in the large-scale study by Van Eck,Waltman,Larivière,and Sugimoto(blog 2018,https://www.cwts.nl/blog?article=n-r2s234).Research limitations:The sample does not cover all science areas uniformly;it is heavily focused on Engineering and Technology,and only some disciplines of Natural Sciences are present.However,this reflects the real scientific orientation and publication profile of our institution.Practical implications:The current level of coverage is not sufficient for the WoS to be replaced by COCI for research evaluation.Originality/value:The present study illustrates a COCI vs WoS comparison on the scale of a larger technical university in Central Europe.
基金supported by the National Natural Science Foundation of China,Grant numbers 71573225 and 71974167。
文摘Purpose:Providing an overview of types of citation curves.Design/methodology/approach:The terms citation curves or citation graphs are made explicit.Findings:A framework for the study of diachronous(and synchronous)citation curves is proposed.Research limitations:No new practical applications are given.Practical implications:This short note about citation curves will help readers to make the optimal choice for their applications.Originality/value:A new scheme for the meaning of the term"citation curve"is designed.
文摘Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals,researchers,institutions,and countries.Authors cite papers for different reasons,such as extending previous work,comparing their study with the state-of-the-art,providing background of the field,etc.In recent years,researchers have tried to conceptualize all citations into two broad categories,important and incidental.Such a categorization is very important to enhance scientific output in multiple ways,for instance,(1)Helping a researcher in identifying meaningful citations from a list of 100 to 1000 citations(2)Enhancing the impact factor calculation mechanism by more strongly weighting important citations,and(3)Improving researcher,institutional,and university rankings by only considering important citations.All of these uses depend upon correctly identifying the important citations from the list of all citations in a paper.To date,researchers have utilized many features to classify citations into these broad categories:cue phrases,in-text citation counts,and metadata features,etc.However,contemporary approaches are based on identification of in-text citation counts,mapping sections onto the Introduction,Methods,Results,and Discussion(IMRAD)structure,identifying cue phrases,etc.Identifying such features accurately is a challenging task and is normally conducted manually,with the accuracy of citation classification demonstrated in terms of these manually extracted features.This research proposes to examine the content of the cited and citing pair to identify important citing papers for each cited paper.This content similarity approach was adopted from research paper recommendation approaches.Furthermore,a novel section-based content similarity approach is also proposed.The results show that solely using the abstract of the cited and citing papers can achieve similar accuracy as the stateof-the-art approaches.This makes the proposed approach a viable technique that does not depend on manual identification of complex features.
文摘Citations based relevant research paper recommendations can be generated primarily with the assistance of three citation models:(1)Bibliographic Coupling,(2)Co-Citation,and(3)Direct Citations.Millions of new scholarly articles are published every year.This flux of scientific information has made it a challenging task to devise techniques that could help researchers to find the most relevant research papers for the paper at hand.In this study,we have deployed an in-text citation analysis that extends the Direct Citation Model to discover the nature of the relationship degree-ofrelevancy among scientific papers.For this purpose,the relationship between citing and cited articles is categorized into three categories:weak,medium,and strong.As an experiment,around 5,000 research papers were crawled from the CiteSeerX.These research papers were parsed for the identification of in-text citation frequencies.Subsequently,0.1 million references of those articles were extracted,and their in-text citation frequencies were computed.A comprehensive benchmark dataset was established based on the user study.Afterwards,the results were validated with the help of Least Square Approximation by Quadratic Polynomial method.It was found that degreeof-relevancy between scientific papers is a quadratic increasing/decreasing polynomial with respect to-increase/decrease in the in-text citation frequencies of a cited article.Furthermore,the results of the proposed model were compared with state-of-the-art techniques by utilizing a well-known measure,known as the normalized Discount Cumulative Gain(nDCG).The proposed method received an nDCG score of 0.89,whereas the state-of-the-art models such as the Content,Bibliographic-coupling,and Metadata-based Models were able to acquire the nDCG values of 0.65,0.54,and 0.51 respectively.These results indicate that the proposed mechanism may be applied in future information retrieval systems for better results.
文摘Recent time handling uncertainty and its measurement is considered as one of the major issues by data science and applied mathematics researchers. It becomes more complex when the dynamicity exists in data sets. One of the suitable examples is Scopus data sets which changes every time. In this case, precise measurement of consistency in document and citation publications is considered as one of the issues. It becomes more complex when the parameter like h-index and document count can be also manipulated over the period of time. To resolve this issue, a time-based index called as “t-index” is illustrated in this paper with an example. This method measures the randomness in document publication and citation using the average h-index and its entropy measurement.
