Exploring the Relationship Between Patent Forward Citation and Stock Return Rate Using Empirical Data of China Stock Market

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.

General laws of funding for scientific citations:how citations change in funded and unfunded research between basic and applied sciences

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.

Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

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.

Citation and bibliographic coupling between authors in the field of social network analysis

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.

Citation distributions and research evaluations:The impossibility of formulating a universal indicator

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.

Tracking direct and indirect impact on technology and policy of transformative research via ego citation network

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.

Research funding and citations in papers of Nobel Laureates in Physics, Chemistry and Medicine, 2019-2020

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.

基于Citation Topic的领域期刊主题演化研究——以行为医学为例

基于论文层面的Citation Topic分类体系,通过测度行为医学领域SCI及SSCI期刊引文主题变动情况,展现国际行为医学领域研究重点以及相关支撑学科的演化。

Functions of Uni- and Multi-citations： Implications for Weighted Citation Analysis

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.

InCites中Citation Topics功能应用于科技期刊选题策划的实证研究——以热带医学研究领域为例

以热带医学研究领域为例,探索InCites数据库中的Citation Topics功能在选题策划中的应用。选取Web of Science数据库中热带医学领域近5年SCIE收录的论文,利用Citation Topics,对个别发文量多或被引频次高的研究方向、区域、研究人员、机构进行微观主题举例分析。疟疾微观主题下表现最活跃的区域为USA,机构为University of London,研究人员为Drakeley,Chris,出版物为Malaria Journal,United States Department of Health&Human Services为疟疾微观主题提供的基金资助最多;血吸虫病、疟疾、登革热、包虫囊肿和冠状病毒是中国热带医学领域的研究重点,冠状病毒、血吸虫病、隐孢子虫、登革热和疟疾微观主题的论文影响力相对较高;研究人员Zhou,Xiao-Nong的重点研究方向为血吸虫病、疟疾和包虫囊肿,疟疾、登革热、轮状病毒、犬弓首线虫和莱姆病研究主题的论文质量和关注度高;University of London热带医学领域的研究重点为疟疾、血吸虫病和登革热。InCites中Citation Topics功能可以实现对研究主题、人员、机构、国家/地区等模块进行更精细的分析,有助于科技期刊编辑更高效地制定选题方案。

WIMS/CITATION在IHNI-1堆芯物理计算中的应用

建立了利用WIMS+CITATION计算医院中子照射器Ⅰ型堆堆芯中子学参数的模型,计算了堆芯的功率分布、顶铍反应性价值、控制棒价值、温度系数、堆芯燃耗等中子学参数,计算结果与文献数据一致,表明文章所建立的计算模型可用于医院中子照射器I型堆堆芯的物理计算。

A New Citation Recommendation Strategy Based on Term Functions in Related Studies Section

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.

Can Crossref Citations Replace Web of Science for Research Evaluation?The Share of Open Citations

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.

Describing Citations as a Function of Time

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.

Exploiting Structural Similarities to Classify Citations

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.

Extension of Direct Citation Model Using In-Text Citations

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.

Writer Stance in Citations: An Ethnolinguistic and Paradigmatic Perspective

This study examines how writer stance is projected in citation from a comparative perspective.The dataset consisted of 120 qualitative and quantitative research articles(RAs)that were authored by Anglophone and Chinese applied linguists.ANO?VA tests revealed marked cross-language and cross-paradigmatic differences in stance-based dialogic engagement.

The Consistency Measurement in Document Publications and Citation Using t-Index

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.

An Informetric analysis of web citation in Chinese journals of Library and Information Science in recent years

This paper selects 998 articles as its data sources from four Chinese core journals in the field of Library and Information Science from 2003 to 2007.Some pertinent aspects of reference citations particularly from web resources are selected for a focused analysis and discussion.This includes primarily such items as the number of web citations,web citations per each article,the distribution of domain names of web citations and also certain aspects about the institutional and/or geographical affiliations of the author.The evolving situation of utilizing online networked academic information resources in China is the central thematic discussion of this study.The writing of this paper is augmented by the explicatory presentation of 3 graphic figures,6 tables and 18 references.

Patent Citations Analysis and Its Value in Research Evaluation： A Review and a New Approach to Map Technology-relevant Research

Purpose： First, to review the state-of-the-art in patent citation analysis, particularly characteristics of patent citations to scientific literature （scientific non-patent references, SNPRs）. Second, to present a novel mapping approach to identify technology-relevant research based on the papers cited by and referring to the SNPRs. Design/methodology/approach： In the review part we discuss the context of SNPRs such as the time lags between scientific achievements and inventions. Also patent-to-patent citation is addressed particularly because this type of patent citation analysis is a major element in the assessment of the economic value of patents. We also review the research on the role of universities and researchers in technological development, with important issues such as universities as sources of technological knowledge and inventor-author relations. We conclude the review part of this paper with an overview of recent research on mapping and network analysis of the science and technology interface and of technological progress in interaction with science. In the second part we apply new techniques for the direct visualization of the cited and citing relations of SNPRs, the mapping of the landscape around SNPRs by bibliographic coupling and co-citation analysis, and the mapping of the conceptual environment of SNPRs by keyword co-occurrence analysis. Findings： We discuss several properties of SNPRs. Only a small minority of publications covered by the Web of Science or Scopus are cited by patents, about 3%-4%. However, for publications based on university-industry collaboration the number of SNPRs is considerably higher, around 15%. The proposed mapping methodology based on a ＂second order SNPR approach＂ enables a better assessment of the technological relevance of research. Research limitations： The main limitation is that a more advanced merging of patent and publication data, in particular unification of author and inventor names, in still a necessity. Practical implications： The proposed mapping methodology enables the creation of a database of technology-relevant papers （TRPs）. In a bibliometric assessment the publications of research groups, research programs or institutes can be matched with the TRPs and thus the extent to which the work of groups, programs or institutes are relevant for technological development can be measured. Originality/value： The review part examines a wide range of findings in the research of patent citation analysis. The mapping approach to identify a broad range of technologyrelevant papers is novel and offers new opportunities in research evaluation practices.