The scientific publications of the 15 West African countries published from 2011 to 2020 were analysed.The co-authorship,the total publications per year,the collaboration rate,the relative specialisation index,and the...The scientific publications of the 15 West African countries published from 2011 to 2020 were analysed.The co-authorship,the total publications per year,the collaboration rate,the relative specialisation index,and the intraregional production were analysed.It comes out that the region produces more than one hundred thousand papers in ten years,which means more than ten thousand per year,tripling its performance as compared with the previous decade.The number of co-authors per paper increases and rises from 4.6 to 6.4.The international collaboration rate is 58%,suggesting that the region's publishing activity depends more on abroad,even though differences were registered at individual country level:some countries multiply by more than 10 their production as compared to the previous decade.The intraregional collaboration is still low(around 5%),meaning that the region's countries do not collaborate with each other and prefer abroad.As far as fields of science are concerned,it appears that the domestic papers perform better in Humanities and Social sciences,whereas the internationally co-authored papers perform better in Natural sciences and Engineering and technology and lesser in Agricultural sciences and Medical and health sciences.展开更多
Two journal-level indicators,respectively the mean(mi)and the standard deviation(vi)are proposed to be the core indicators of each journal and we show that quite several other indicators can be calculated from those t...Two journal-level indicators,respectively the mean(mi)and the standard deviation(vi)are proposed to be the core indicators of each journal and we show that quite several other indicators can be calculated from those two core indicators,assuming that yearly citation counts of papers in each journal follow more or less a log-normal distribution.Those other journal-level indicators include journal index,journal one-by-one-sample comparison citation success index S_(j)^(i),journal multiple-sample K^(i)-K^(j) comparison success rate S_(j,k^(j)^(i,k^(i))),and minimum representative sizes k_(j)^(i) and k_(i)^(j),the average ranking of all papers in a journal in a set of journals(R^(t)).We find that those indicators are consistent with those calculated directly using the raw citation data({C^(i)=(c_(1)^(i),c_(2)^(j),...c_(N)^(i),■i})of journals.In addition to its theoretical significance,the ability to estimate other indicators from core indicators has practical implications.This feature enables individuals who lack access to raw citation count data to utilize other indicators by simply using core indicators,which are typically easily accessible.展开更多
In the last decades many methods have been developed for the evaluation of the quality and impact of both the scientific research papers and scientists.Effectively identifying,discovering,and evaluating high-impact pa...In the last decades many methods have been developed for the evaluation of the quality and impact of both the scientific research papers and scientists.Effectively identifying,discovering,and evaluating high-impact papers using scientometric methods,and adopting reasonable evaluation procedures and methods are vital to stimulating scientists’creative vitality.Examples of methods used for evaluating impact are:h-index and the cited frequency of articles and the number of highly cited papers.Here we propose a new method to assess the scientist impact based on citation iteration.The method was inspired in the Page Rank algorithm.In the present study,both the number of citations and the citing publications after each citation were considered.According to the obtained results,the proposal allows a more accurate measurement of the impact of scientific papers.Also,the application of this method,it can greatly improve the judgment efficiency of high-impact scientists.We have also conducted an empirical study at three levels in the discipline of mathematics,namely the comparisons of two publications,two scientists and eight scientists.Results show that indexes proposed in this dissertation designed for the publications’impacts evaluation and scientists’impact evaluation can be used to find the cause behind the number of cited frequencies resulting in the impact difference.The Q-index for publications’impacts evaluation and F-index for scientists’impacts evaluation proposed in this article can be used more accurately to check and evaluate the impact of scientists.Additionally,these new indexes can be used in the research management of departments at all levels,and can be useful by the states to find leading scientists in several fields.展开更多
Citation Context Analysis(CCA)is a typical data-driven research field based on full-text information,which breaks the limitations of traditional citation analysis using only bibliographic data,and benefits further stu...Citation Context Analysis(CCA)is a typical data-driven research field based on full-text information,which breaks the limitations of traditional citation analysis using only bibliographic data,and benefits further studies on various citation behaviors and other core issues behind them,such as citation motivation,citation function and citation sentiment.Corpus for CCA is the most important guarantee and support for these issues.This paper attempts to discuss the corpus construction and mining for CCA in order to comprehensively review the research significance,research status and existing deficiencies in this area.Two main sections in our paper are:1)corpus construction for CCA,its three building tasks,such as citation sentence extraction,citation-reference mapping and citation context extraction,are discussed;2)corpus mining and utilization for CCA,following related topics or situations are explored,including classification of citation motivation(or behavior)and citation sentiment,indexing and retrieval based on citation,citation recommendation and evaluation,citation-based abstracting and review generation automatically,and domains knowledge metrics.Finally,some suggestions and future research directions are briefly listed.展开更多
The entering into big data era gives rise to a novel discipline called Data Science.Data Science is interdisciplinary in its nature,and the existing relevant studies can be categorized into domain-independent studies ...The entering into big data era gives rise to a novel discipline called Data Science.Data Science is interdisciplinary in its nature,and the existing relevant studies can be categorized into domain-independent studies and domain-dependent studies.The domain-dependent studies and domain-independent ones are evolving into Domain-general Data Science and Domain-specific Data Science.Domain-general Data Science emphasizes Data Science in a general sense,involving concepts,theories,methods,technologies,and tools.Domain-specific Data Science is a variant of Domain-general Data Science and varies from one domain to another.The most popular Domain-specific Data Science includes Data journalism,Industrial Data Science,Business Data Science,Health Data Science,Biological Data Science,Social Data Science,and Agile Data Science.The difference between Domain-general Data Science and Domain-specific Data Science roots in their thinking paradigms:DGDS conforms to data-centered thinking,while DSDS is in line with knowledge-centered thinking.As a result,DGDS focuses on the theoretical studies,while DSDS is centered on applied ones.However,DSDS and DGDS possess complementary advantages.Theoretical Data Science(TDS)is a new branch of Data Science that employs mathematical models and abstractions of data objects and systems to rationalize,explain and predict big data phenomena.TDS will bridge the gap between DGDS and DSDS.TDS contrasts with DSDS,which uses casual analysis,as well as DGDS,which employs data-centered thinking to deal with big data problems in that it balances the usability and the interpretability of Data Science practices.The main concerns of TDS are concentrated on integrating the data-centered thinking with the knowledge-centered thinking as well as transforming a correlation analysis into the casual analysis.Hence,TDS can bridge the gaps between DGDS and DSDS,and balance the usability and the interpretability of big data solutions.The studies of TDS should be focused on the following research purpose:to develop theoretical studies of TDS,to take advantages of active property of big data,to embrace design of experiments,to enhance causality analysis,and to develop data products.展开更多
To establish a data literacy evaluation system for social science scholars is a part of transformation to data-intensive scientific research paradigm in social science.Based on the literature review of data literacy a...To establish a data literacy evaluation system for social science scholars is a part of transformation to data-intensive scientific research paradigm in social science.Based on the literature review of data literacy and survey of social science data management features,this paper analyzed the elements of data literacy of social science scholars.The data literacy of social science scholars ma inly consists of data awareness level,data discovery and access ability,data management and organization ability,data processing and analysis ability,data utilization and preservation ability,and data ethics level.Each of these primary indexes has several secondary indexes.It constructed the evaluation system of social science scholars data literacy.The weights of the primary and secondary indexes in the system were calculated by applying AHP.The data literacy evaluation system for social science scholars can provide a reference for assessing and promoting social science scholars'data literacy ability in China.展开更多
It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on th...It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on the in-depth analysis of the existing research,this paper finds that patent quality is the inherent decisive factor of patent transferability.Combining with the evaluation indexes of patent quality and the bibliometrics characteristics of university patents,9 indicators are proposed to indicate the transferability of university patents.Based on the patent transfer data of 35 Chinese universities,this paper analyzes and verifies the potential indicators of patent transfer using the binary logistic regression method.The results show that the number of inventors and the number of non-patent document citations positively predict the transferability of university patents,while the examination duration negatively predicts transferability.The effects of other indicators on transferability need to be discussed considering the actual situation and specific technology fields.展开更多
With the development of open access,more scientific papers show the multi-dimensional academic impact,which makes researchers focus on the comparison between altmetrics and citations.By the use of statistical analysis...With the development of open access,more scientific papers show the multi-dimensional academic impact,which makes researchers focus on the comparison between altmetrics and citations.By the use of statistical analysis,we compare the citation and altmetrics of open access papers published in PLoS in past 10 years by 6 countries which are selected in terms of regional distribation,scientific level,native language,etc.,and find the following conclusions:Firstly,the level of scientific development and publication content in different countries have more effect on the 4 indicators of"citation","save","view"and"share"than the native language.Second,there is a significantly positive correlation between"citation"and"save"in the 6 countries,so as the"citation"and"view",while the altmetrics of"share"is just opposite.Therefore,to some extent,the altmetrics of"view"and"save"could be used to evaluate the scientific influence as a complement measurement of traditional citation metrics.Moreover,correlation coefficients between citations and part of altmetrics of the 6 countries are strong.Finally,the curve peaks of the 6 countries occurred in different years,papers published by developed countries have been active for slightly longer than that by developing countries.In detail,the"citation","save"and"view"peaks occurred later in developing countries such as China and Brazil than in some developed countries.Besides,the"share"peak occurred after 6 or 7 years,which is similar for the 6 countries.展开更多
With the deep meaning of discourse power in international relations,national discourse power has become an important manifestation of national soft power.This paper analyzes the main elements of the discourse power of...With the deep meaning of discourse power in international relations,national discourse power has become an important manifestation of national soft power.This paper analyzes the main elements of the discourse power of patentee to speak,constructs the evaluation model,and selects the evaluation indexes related to the six characteristics according to the methods of patent measurement and social network analysis.In the empirical research stage,taking the field of network security as an example,the validity and reliability of the evaluation system are tested,and the accuracy of the evaluation results is tested by correlation.It is found that the evaluation system of discourse power of patentee to speak in the field of network security proposed in this paper is effective.展开更多
Algorithms play an increasingly important role in scientific work,especially in data-driven research.Investigating the mention of algorithms in full-text paper helps us understand the use and development of algorithms...Algorithms play an increasingly important role in scientific work,especially in data-driven research.Investigating the mention of algorithms in full-text paper helps us understand the use and development of algorithms in a specific domain.Current research on the mention of algorithms is limited to the academic papers in one language,which is hard to comprehensively investigate the use of algorithms.For example,in papers of Chinese conference,is the mention of algorithms consistent with it in English conference papers?In order to answer this question,this paper takes NLP as an example,and compares the mention frequency,mention location and mention time of the top10 data-mining algorithms between the papers of the famous international conference,Annual Meeting of the Association for Computational Linguistics(ACL),and the Chinese conference,China National Conference on Computational Linguistics(CCL).The results show that compared with ACL,the mention frequency of top10 data-mining algorithms in CCL is slightly lower and the mention time is slightly delayed,while the distribution of mention location is similar.This study can provide a reference for the research related to the mention,citation and evaluation of knowledge entities.展开更多
[Purpose/significance]Interdisciplinary knowledge fusion plays a key role in promoting the development of interdisciplinary integration and providing new ideas for interdisciplinary cooperative research.This study set...[Purpose/significance]Interdisciplinary knowledge fusion plays a key role in promoting the development of interdisciplinary integration and providing new ideas for interdisciplinary cooperative research.This study sets out to identify potential interdisciplinary cooperative topics between Library and Information Science(LIS)and Computer Science.[Method/Process]We built an interdisciplinary co-word network to identify potential interdisciplinary cooperative topics by closed and opened irrelevant knowledge discovery methods.We also constructed the topic interdisciplinary cooperation potential index(TICPI)to calculate the interdisciplinary cooperation potential of the topic and found the best contact path of the cooperation topic by constructing the practicable value(PV)of the contact patch.[Result/Conclusion]The experimental data suggested that both methods can identify the same potential interdisciplinary cooperative topics,such as knowledge service&matrix decomposition,online comments&social media processing,academic text&generative adversarial network,network public opinion&smart home.Exploiting the cooperation potential of these topics can help the knowledge fusion between disciplines.展开更多
Here we report on a study that combined a scoping review with co-occurrence analysis to assess the current state of publications and research topics in the area of international research collaboration measurement(IRCM...Here we report on a study that combined a scoping review with co-occurrence analysis to assess the current state of publications and research topics in the area of international research collaboration measurement(IRCM).Our study found that IRCM studies have been published in source titles of diverse subject areas and that there are two core research topics that have been commonly discussed across different subject areas in the IRCM domain-scientific productivity measurement and scientific impact measurement.The appearance of papers about IRCM in venues beyond those concerned only with bibliometric measures indicates the broad importance of IRCM for diverse research subjects,and that studies of IRC within particular fields should draw on diverse venues to provide a holistic and interdisciplinary picture of IRCM.展开更多
[Purpose/Significance]The purpose is to explore the use of We Chat official accounts articles(referred to as We Chat articles)as a type of Chinese altmetrics data source,and reveal the attention and discussion surroun...[Purpose/Significance]The purpose is to explore the use of We Chat official accounts articles(referred to as We Chat articles)as a type of Chinese altmetrics data source,and reveal the attention and discussion surrounding altmetrics in the social media environment,as well as discover the similarities and dissimilarities compared to that of scholarly publications.[Methodology/Procedure]Using We Chat articles that are relevant to altmetrics as the research object,statistical analysis,quantitative analysis,and text mining were used to explore the pattern of attention and discussion of altmetrics in We Chat articles.Meanwhile,scholarly publications of altmetrics were collected for scientometric analysis.The similarities and dissimilarities as regards the degree of attention,topic distribution and developing trend were compared between these two datasets.[Results/Conclusions](1)Number of We Chat articles that mention altmetrics is increasing rapidly,although there is a time lag between the first We Chat article and the first scholarly publication of altmetrics.(2)Types of We Chat official accounts that pay attention to altmetrics are very diversified and go beyond the academia.(3)We Chat articles relevant to altmetrics mainly focus on 4 topics,i.e.the introduction of the latest publications of altmetrics,information of relevant scholarly activities and scholarly meetings,informetrics research and scientific evaluation that involve altmetrics,and introduction of altmetrics monographs.(4)Four major types of context where altmetrics is mentioned by We Chat articles are identified.They are to introduce the concept,theory,knowledge system,and technical methods of altmetrics,to discuss the data sources and research objects of altmetrics,to discuss the construction and application of altmetrics indicators,and to discuss the meaning and value of altmetrics.(5)In contrast,scholarly publications of altmetrics are more centered on systematic research,including the theories of altmetrics,the construction of altmetrics indicators,the application of altmetrics indicators,impact evaluation,and the relationship between altmetrics and traditional informetrics.These results are useful for further developing the Chinese altmetrics data source and understanding the relationship between altmetrics and bibliometrics.展开更多
Revealing and comparing the evolution process of hot topics in the field of Digital Library in China and abroad.[Methods]:Taking data in the field of Digital Library from core journals in CKNI and Web of Science from ...Revealing and comparing the evolution process of hot topics in the field of Digital Library in China and abroad.[Methods]:Taking data in the field of Digital Library from core journals in CKNI and Web of Science from 1990 s to 2020,topics are extracted by LDA model and hot topics are selected based on life cycle theory.Topic evolution paths are generated to contrast evolution of hot topics between home and abroad which are grouped into dimensions of technology and application.It fails to analyze the lagging performance and reasons of research hot topics in the field of Digital Library at home and abroad.In technological dimension of Digital Library,the research content in China lags behind that at abroad.In terms of application dimension,Chinese application tends to focus on social sciences,while application at abroad tends to focus on natural sciences.The evolution of overall research focus is U-shaped,which gradually shifted from technological research to application research,and now turn back to technological dimension.Nowadays,there are also many emerging topics combined with big data technology.展开更多
Data science is an emerging interdisciplinary subject in the era of big data,integrating knowledge in many fields such as machine learning,statistics,and data visualization.By analyzing the output and basic characteri...Data science is an emerging interdisciplinary subject in the era of big data,integrating knowledge in many fields such as machine learning,statistics,and data visualization.By analyzing the output and basic characteristics of data science papers from 2015 to 2021,this paper examines the influence of author country,open access status,discipline category,literature type,publication year,and research hotspot on the number of citations and social attention score of data science papers.The results show that data science papers continue to increase annually,with the highest number in 2017.The authors are mainly from the United States,England,Germany,and China,and accordingly mainly from North America,Europe,and Asia.Article,Review and Editorial’s material are the main types of papers.Open-access papers are nearly twice as likely as non-open-access papers;Statistical analysis further confirmed that publication age and literature type had significant influence on citation times.The age of the paper,the type of the paper,the country of the author,the state of open access,and the discipline category have a significant influence on the score of social concern.Then,the comparison of keyword co-occurrence clustering diagram between highly cited papers and papers with high social attention shows that there are similarities and differences between the research hotspots of highly cited papers and papers with high social attention.The similarities are that machine learning,big data visualization and big data analysis of electronic health records are common research hotspots.While the difference is that highly cited data science papers also focus on big data analysis of business competitive advantage and big data analysis of social media.Data science papers with high AAS scores focus on open science big data analysis,bio in fo rmatics big data analysis,and reproducible research as well.展开更多
HFMD can be caused by a variety of enteroviruses,including Coxsackievirus A16 and enterovirus71.There are no effective therapeutic measures to cure HFMD at present.So,this study aimed to analyze the spatial relativity...HFMD can be caused by a variety of enteroviruses,including Coxsackievirus A16 and enterovirus71.There are no effective therapeutic measures to cure HFMD at present.So,this study aimed to analyze the spatial relativity and the local accumulation type based on the theory of spatial analysis and the spatial autocorrelation analysis module of ArcGIS and Geo Da.We found that there was a seasonal trend in HFMD.The lowest incidence appeared in February,and the peak of the reported incidence was occurred during the period from May to June.However,in most cases,another peak appeared from September to November.The trend of incidence was related to age,too.The overall trend of the reported incidence was a U-shape in north-south orientation and exposed an inverted U-shape in east-west.The correlation between the spatial distribution of HFMD was positive.Hunan,Guangxi and Guangdong were the hot areas,while the cold spots were Jilin,Inner Mongolia,Xinjiang,Gansu and Qinghai.展开更多
With the rapid development of Internet technology,a rich set of e-government data are collected by the government departments.For example,a variety of feedback text data can be obtained quickly and efficiently through...With the rapid development of Internet technology,a rich set of e-government data are collected by the government departments.For example,a variety of feedback text data can be obtained quickly and efficiently through various channels such as the mayor’s mailbox.It is an effective way to improve the working efficiency of the government to extract hot topics from large-scale e-government text data,establish the correlation between topics and geographic space,and interactively explore the sources of public feedback problems.However,it is a difficult task to explore the large-scale e-government text data with traditional visualization methods such as word cloud,because too many words are hardly distributed in a limited space which will largely disturb the visual perception.In this paper,we propose a visual analytics system for large-scale e-government data exploration by means of simplified word cloud.Firstly,a representation learning model is used to embed the text data into high-dimensional space to quantitatively represent the semantic structure features of e-government text data.Then,the high-dimensional vectors are projected into a two-dimensional space where the coordinate distribution of points effectively expresses the semantic similarity of original words,which also presents geographic features that can be quantized by means of a similarity computing model.In order to simplify the understanding of large-scale e-government data and improve the cognitive efficiency of word could,we adopt the adaptive blue noise method to sample the topic words,which can simplify the visual expression of word cloud and improve the understanding efficiency of e-government data without losing the semantic structure features.Furthermore,an abstraction and visual analysis system for large-scale e-government text data is designed and implemented by integrating the above representation learning model,sampling-based abstraction model of word cloud,and topic and geographic correlation analysis model.This system provides convenient human-computer interaction modes and supports users to explore the analysis and extraction of the characteristics hidden in large-scale e-government data.It also helps government departments quickly locate the hot topics of public concern and their related regional distribution,and provides decision support to further improve the work efficiency of the government.Case studies based on real-world datasets further verify the effectiveness and practicability of our system.展开更多
It has been evidenced that peer review activities are positively correlated to scientists’bibliometric performance(e.g.,Ortega,2017,2019).However,how the number of paper’reviewing’interacts with a scientist’s’pub...It has been evidenced that peer review activities are positively correlated to scientists’bibliometric performance(e.g.,Ortega,2017,2019).However,how the number of paper’reviewing’interacts with a scientist’s’publishing’has not been addressed in previous studies.This paper attempts to employ the Granger causality inference to explore the directionality between a scientist’s publication performance and his/her review activities.Our dataset comprises scientists’reviewed articles derived from Publons in the Web of Knowledge database,and their publications retrieved from Pub Med.We find that scientists who reviewed less or published less tend to have Granger causality between reviewing and publishing activities.In addition,compared with early-career researchers,reviewing advances publishing for senior scientists.展开更多
The e-commerce standard internationalization has become the strategic targets of China’s digital economy.This paper proposes the system dynamics model through analyzing the internal and external factors of e-commerce...The e-commerce standard internationalization has become the strategic targets of China’s digital economy.This paper proposes the system dynamics model through analyzing the internal and external factors of e-commerce standard internationalization under dynamic mechanism.The internationalization trend of China’s e-commerce standard is simulated by Vensim under adjusting economy factor,policy support factor,technical-innovation factor and industry supply chain’s service factor.The experiment results show that China’s international leadership on e-commerce and its influence on standard internationalization from the top-level design,strengthen industry supply chain’s standard certification and the technical-innovation of product standard factors,which can promote the high quality made-in-China brand.展开更多
In recent years,with the rapid development and expansion of postgraduate education in China,the cultivation quality has become increasingly prominent.In graduate education activities,there are many factors that affect...In recent years,with the rapid development and expansion of postgraduate education in China,the cultivation quality has become increasingly prominent.In graduate education activities,there are many factors that affect the quality of cultivation,among which the tutor’s guiding ability is undoubtedly the key factor that affects the quality of graduate students’cultivation.In the 2020 National Graduate Education Conference,one of its topics is how to objectively quantify the guiding ability of supervisors based on which the teaching resources can be optimally allocated.Taking Hangzhou Dianzi University as an example,this paper investigates the index systems to evaluate the guiding ability of graduate students’supervisors including 6 first-level indicators and 19 second-level indicators in order to further improve the cultivation performance of graduate students.展开更多
文摘The scientific publications of the 15 West African countries published from 2011 to 2020 were analysed.The co-authorship,the total publications per year,the collaboration rate,the relative specialisation index,and the intraregional production were analysed.It comes out that the region produces more than one hundred thousand papers in ten years,which means more than ten thousand per year,tripling its performance as compared with the previous decade.The number of co-authors per paper increases and rises from 4.6 to 6.4.The international collaboration rate is 58%,suggesting that the region's publishing activity depends more on abroad,even though differences were registered at individual country level:some countries multiply by more than 10 their production as compared to the previous decade.The intraregional collaboration is still low(around 5%),meaning that the region's countries do not collaborate with each other and prefer abroad.As far as fields of science are concerned,it appears that the domestic papers perform better in Humanities and Social sciences,whereas the internationally co-authored papers perform better in Natural sciences and Engineering and technology and lesser in Agricultural sciences and Medical and health sciences.
文摘Two journal-level indicators,respectively the mean(mi)and the standard deviation(vi)are proposed to be the core indicators of each journal and we show that quite several other indicators can be calculated from those two core indicators,assuming that yearly citation counts of papers in each journal follow more or less a log-normal distribution.Those other journal-level indicators include journal index,journal one-by-one-sample comparison citation success index S_(j)^(i),journal multiple-sample K^(i)-K^(j) comparison success rate S_(j,k^(j)^(i,k^(i))),and minimum representative sizes k_(j)^(i) and k_(i)^(j),the average ranking of all papers in a journal in a set of journals(R^(t)).We find that those indicators are consistent with those calculated directly using the raw citation data({C^(i)=(c_(1)^(i),c_(2)^(j),...c_(N)^(i),■i})of journals.In addition to its theoretical significance,the ability to estimate other indicators from core indicators has practical implications.This feature enables individuals who lack access to raw citation count data to utilize other indicators by simply using core indicators,which are typically easily accessible.
基金funded by the National Social Science Foundation of China-Community Research on Hybrid Networks for Scientific Structure Analysis(Grant No.19XTQ012)the National Key Research and Development Program of China(Grant No.2017YFB1402400)
文摘In the last decades many methods have been developed for the evaluation of the quality and impact of both the scientific research papers and scientists.Effectively identifying,discovering,and evaluating high-impact papers using scientometric methods,and adopting reasonable evaluation procedures and methods are vital to stimulating scientists’creative vitality.Examples of methods used for evaluating impact are:h-index and the cited frequency of articles and the number of highly cited papers.Here we propose a new method to assess the scientist impact based on citation iteration.The method was inspired in the Page Rank algorithm.In the present study,both the number of citations and the citing publications after each citation were considered.According to the obtained results,the proposal allows a more accurate measurement of the impact of scientific papers.Also,the application of this method,it can greatly improve the judgment efficiency of high-impact scientists.We have also conducted an empirical study at three levels in the discipline of mathematics,namely the comparisons of two publications,two scientists and eight scientists.Results show that indexes proposed in this dissertation designed for the publications’impacts evaluation and scientists’impact evaluation can be used to find the cause behind the number of cited frequencies resulting in the impact difference.The Q-index for publications’impacts evaluation and F-index for scientists’impacts evaluation proposed in this article can be used more accurately to check and evaluate the impact of scientists.Additionally,these new indexes can be used in the research management of departments at all levels,and can be useful by the states to find leading scientists in several fields.
文摘Citation Context Analysis(CCA)is a typical data-driven research field based on full-text information,which breaks the limitations of traditional citation analysis using only bibliographic data,and benefits further studies on various citation behaviors and other core issues behind them,such as citation motivation,citation function and citation sentiment.Corpus for CCA is the most important guarantee and support for these issues.This paper attempts to discuss the corpus construction and mining for CCA in order to comprehensively review the research significance,research status and existing deficiencies in this area.Two main sections in our paper are:1)corpus construction for CCA,its three building tasks,such as citation sentence extraction,citation-reference mapping and citation context extraction,are discussed;2)corpus mining and utilization for CCA,following related topics or situations are explored,including classification of citation motivation(or behavior)and citation sentiment,indexing and retrieval based on citation,citation recommendation and evaluation,citation-based abstracting and review generation automatically,and domains knowledge metrics.Finally,some suggestions and future research directions are briefly listed.
基金the Ministry of education of Humanities and Social Science project(Project No.20YJA870003)
文摘The entering into big data era gives rise to a novel discipline called Data Science.Data Science is interdisciplinary in its nature,and the existing relevant studies can be categorized into domain-independent studies and domain-dependent studies.The domain-dependent studies and domain-independent ones are evolving into Domain-general Data Science and Domain-specific Data Science.Domain-general Data Science emphasizes Data Science in a general sense,involving concepts,theories,methods,technologies,and tools.Domain-specific Data Science is a variant of Domain-general Data Science and varies from one domain to another.The most popular Domain-specific Data Science includes Data journalism,Industrial Data Science,Business Data Science,Health Data Science,Biological Data Science,Social Data Science,and Agile Data Science.The difference between Domain-general Data Science and Domain-specific Data Science roots in their thinking paradigms:DGDS conforms to data-centered thinking,while DSDS is in line with knowledge-centered thinking.As a result,DGDS focuses on the theoretical studies,while DSDS is centered on applied ones.However,DSDS and DGDS possess complementary advantages.Theoretical Data Science(TDS)is a new branch of Data Science that employs mathematical models and abstractions of data objects and systems to rationalize,explain and predict big data phenomena.TDS will bridge the gap between DGDS and DSDS.TDS contrasts with DSDS,which uses casual analysis,as well as DGDS,which employs data-centered thinking to deal with big data problems in that it balances the usability and the interpretability of Data Science practices.The main concerns of TDS are concentrated on integrating the data-centered thinking with the knowledge-centered thinking as well as transforming a correlation analysis into the casual analysis.Hence,TDS can bridge the gaps between DGDS and DSDS,and balance the usability and the interpretability of big data solutions.The studies of TDS should be focused on the following research purpose:to develop theoretical studies of TDS,to take advantages of active property of big data,to embrace design of experiments,to enhance causality analysis,and to develop data products.
基金This research is supported by Chinese National Social Science Key Grant Funding"Big Data-Driven Cloud Platform Construction and Intelligent Service of Science and Education Eval-uation".
文摘To establish a data literacy evaluation system for social science scholars is a part of transformation to data-intensive scientific research paradigm in social science.Based on the literature review of data literacy and survey of social science data management features,this paper analyzed the elements of data literacy of social science scholars.The data literacy of social science scholars ma inly consists of data awareness level,data discovery and access ability,data management and organization ability,data processing and analysis ability,data utilization and preservation ability,and data ethics level.Each of these primary indexes has several secondary indexes.It constructed the evaluation system of social science scholars data literacy.The weights of the primary and secondary indexes in the system were calculated by applying AHP.The data literacy evaluation system for social science scholars can provide a reference for assessing and promoting social science scholars'data literacy ability in China.
基金supported by the National Social Science Foundation of China,A Restudy of patent Citation Relationship and its Evaluation Significance from the Perspective of Innovation Economics(Grant No.20XTQ008)。
文摘It is of great significance to study the indicators of university patents’transferability for improving the efficiency of the University Technology Transfer Office and promoting university patent transfer.Based on the in-depth analysis of the existing research,this paper finds that patent quality is the inherent decisive factor of patent transferability.Combining with the evaluation indexes of patent quality and the bibliometrics characteristics of university patents,9 indicators are proposed to indicate the transferability of university patents.Based on the patent transfer data of 35 Chinese universities,this paper analyzes and verifies the potential indicators of patent transfer using the binary logistic regression method.The results show that the number of inventors and the number of non-patent document citations positively predict the transferability of university patents,while the examination duration negatively predicts transferability.The effects of other indicators on transferability need to be discussed considering the actual situation and specific technology fields.
文摘With the development of open access,more scientific papers show the multi-dimensional academic impact,which makes researchers focus on the comparison between altmetrics and citations.By the use of statistical analysis,we compare the citation and altmetrics of open access papers published in PLoS in past 10 years by 6 countries which are selected in terms of regional distribation,scientific level,native language,etc.,and find the following conclusions:Firstly,the level of scientific development and publication content in different countries have more effect on the 4 indicators of"citation","save","view"and"share"than the native language.Second,there is a significantly positive correlation between"citation"and"save"in the 6 countries,so as the"citation"and"view",while the altmetrics of"share"is just opposite.Therefore,to some extent,the altmetrics of"view"and"save"could be used to evaluate the scientific influence as a complement measurement of traditional citation metrics.Moreover,correlation coefficients between citations and part of altmetrics of the 6 countries are strong.Finally,the curve peaks of the 6 countries occurred in different years,papers published by developed countries have been active for slightly longer than that by developing countries.In detail,the"citation","save"and"view"peaks occurred later in developing countries such as China and Brazil than in some developed countries.Besides,the"share"peak occurred after 6 or 7 years,which is similar for the 6 countries.
文摘With the deep meaning of discourse power in international relations,national discourse power has become an important manifestation of national soft power.This paper analyzes the main elements of the discourse power of patentee to speak,constructs the evaluation model,and selects the evaluation indexes related to the six characteristics according to the methods of patent measurement and social network analysis.In the empirical research stage,taking the field of network security as an example,the validity and reliability of the evaluation system are tested,and the accuracy of the evaluation results is tested by correlation.It is found that the evaluation system of discourse power of patentee to speak in the field of network security proposed in this paper is effective.
基金supported by the National Natural Science Foundation of China(Grant No.72074113)
文摘Algorithms play an increasingly important role in scientific work,especially in data-driven research.Investigating the mention of algorithms in full-text paper helps us understand the use and development of algorithms in a specific domain.Current research on the mention of algorithms is limited to the academic papers in one language,which is hard to comprehensively investigate the use of algorithms.For example,in papers of Chinese conference,is the mention of algorithms consistent with it in English conference papers?In order to answer this question,this paper takes NLP as an example,and compares the mention frequency,mention location and mention time of the top10 data-mining algorithms between the papers of the famous international conference,Annual Meeting of the Association for Computational Linguistics(ACL),and the Chinese conference,China National Conference on Computational Linguistics(CCL).The results show that compared with ACL,the mention frequency of top10 data-mining algorithms in CCL is slightly lower and the mention time is slightly delayed,while the distribution of mention location is similar.This study can provide a reference for the research related to the mention,citation and evaluation of knowledge entities.
基金National Social Science Foundation of China,Research on Identification of Interdisciplinary Potential Knowledge Growth Point and Innovation Trend Forecast(No.19ATQ006)。
文摘[Purpose/significance]Interdisciplinary knowledge fusion plays a key role in promoting the development of interdisciplinary integration and providing new ideas for interdisciplinary cooperative research.This study sets out to identify potential interdisciplinary cooperative topics between Library and Information Science(LIS)and Computer Science.[Method/Process]We built an interdisciplinary co-word network to identify potential interdisciplinary cooperative topics by closed and opened irrelevant knowledge discovery methods.We also constructed the topic interdisciplinary cooperation potential index(TICPI)to calculate the interdisciplinary cooperation potential of the topic and found the best contact path of the cooperation topic by constructing the practicable value(PV)of the contact patch.[Result/Conclusion]The experimental data suggested that both methods can identify the same potential interdisciplinary cooperative topics,such as knowledge service&matrix decomposition,online comments&social media processing,academic text&generative adversarial network,network public opinion&smart home.Exploiting the cooperation potential of these topics can help the knowledge fusion between disciplines.
文摘Here we report on a study that combined a scoping review with co-occurrence analysis to assess the current state of publications and research topics in the area of international research collaboration measurement(IRCM).Our study found that IRCM studies have been published in source titles of diverse subject areas and that there are two core research topics that have been commonly discussed across different subject areas in the IRCM domain-scientific productivity measurement and scientific impact measurement.The appearance of papers about IRCM in venues beyond those concerned only with bibliometric measures indicates the broad importance of IRCM for diverse research subjects,and that studies of IRC within particular fields should draw on diverse venues to provide a holistic and interdisciplinary picture of IRCM.
基金supported by National Natural Science Foundation of China(NO.71804067)Humanity and Social Science Foundation of Ministry of Education of China(18YJC870023)the Fundamental Research Funds for the Central Universities(No.30920021203)
文摘[Purpose/Significance]The purpose is to explore the use of We Chat official accounts articles(referred to as We Chat articles)as a type of Chinese altmetrics data source,and reveal the attention and discussion surrounding altmetrics in the social media environment,as well as discover the similarities and dissimilarities compared to that of scholarly publications.[Methodology/Procedure]Using We Chat articles that are relevant to altmetrics as the research object,statistical analysis,quantitative analysis,and text mining were used to explore the pattern of attention and discussion of altmetrics in We Chat articles.Meanwhile,scholarly publications of altmetrics were collected for scientometric analysis.The similarities and dissimilarities as regards the degree of attention,topic distribution and developing trend were compared between these two datasets.[Results/Conclusions](1)Number of We Chat articles that mention altmetrics is increasing rapidly,although there is a time lag between the first We Chat article and the first scholarly publication of altmetrics.(2)Types of We Chat official accounts that pay attention to altmetrics are very diversified and go beyond the academia.(3)We Chat articles relevant to altmetrics mainly focus on 4 topics,i.e.the introduction of the latest publications of altmetrics,information of relevant scholarly activities and scholarly meetings,informetrics research and scientific evaluation that involve altmetrics,and introduction of altmetrics monographs.(4)Four major types of context where altmetrics is mentioned by We Chat articles are identified.They are to introduce the concept,theory,knowledge system,and technical methods of altmetrics,to discuss the data sources and research objects of altmetrics,to discuss the construction and application of altmetrics indicators,and to discuss the meaning and value of altmetrics.(5)In contrast,scholarly publications of altmetrics are more centered on systematic research,including the theories of altmetrics,the construction of altmetrics indicators,the application of altmetrics indicators,impact evaluation,and the relationship between altmetrics and traditional informetrics.These results are useful for further developing the Chinese altmetrics data source and understanding the relationship between altmetrics and bibliometrics.
文摘Revealing and comparing the evolution process of hot topics in the field of Digital Library in China and abroad.[Methods]:Taking data in the field of Digital Library from core journals in CKNI and Web of Science from 1990 s to 2020,topics are extracted by LDA model and hot topics are selected based on life cycle theory.Topic evolution paths are generated to contrast evolution of hot topics between home and abroad which are grouped into dimensions of technology and application.It fails to analyze the lagging performance and reasons of research hot topics in the field of Digital Library at home and abroad.In technological dimension of Digital Library,the research content in China lags behind that at abroad.In terms of application dimension,Chinese application tends to focus on social sciences,while application at abroad tends to focus on natural sciences.The evolution of overall research focus is U-shaped,which gradually shifted from technological research to application research,and now turn back to technological dimension.Nowadays,there are also many emerging topics combined with big data technology.
基金supported by one of the research results of"Evaluation and Prediction of academic influence,Social Attention,and clinical transfo rmation potential of COVID-19 Scientific Research Achievements",2020 Scientific Research Fund Project of Education Department of Liaoning Province-Young Scientific and Technological Talents"Seedling"project(Project No.QNRW2020004)。
文摘Data science is an emerging interdisciplinary subject in the era of big data,integrating knowledge in many fields such as machine learning,statistics,and data visualization.By analyzing the output and basic characteristics of data science papers from 2015 to 2021,this paper examines the influence of author country,open access status,discipline category,literature type,publication year,and research hotspot on the number of citations and social attention score of data science papers.The results show that data science papers continue to increase annually,with the highest number in 2017.The authors are mainly from the United States,England,Germany,and China,and accordingly mainly from North America,Europe,and Asia.Article,Review and Editorial’s material are the main types of papers.Open-access papers are nearly twice as likely as non-open-access papers;Statistical analysis further confirmed that publication age and literature type had significant influence on citation times.The age of the paper,the type of the paper,the country of the author,the state of open access,and the discipline category have a significant influence on the score of social concern.Then,the comparison of keyword co-occurrence clustering diagram between highly cited papers and papers with high social attention shows that there are similarities and differences between the research hotspots of highly cited papers and papers with high social attention.The similarities are that machine learning,big data visualization and big data analysis of electronic health records are common research hotspots.While the difference is that highly cited data science papers also focus on big data analysis of business competitive advantage and big data analysis of social media.Data science papers with high AAS scores focus on open science big data analysis,bio in fo rmatics big data analysis,and reproducible research as well.
基金the National Natural Social Science Found of China(Grant Nos.17AJY008)
文摘HFMD can be caused by a variety of enteroviruses,including Coxsackievirus A16 and enterovirus71.There are no effective therapeutic measures to cure HFMD at present.So,this study aimed to analyze the spatial relativity and the local accumulation type based on the theory of spatial analysis and the spatial autocorrelation analysis module of ArcGIS and Geo Da.We found that there was a seasonal trend in HFMD.The lowest incidence appeared in February,and the peak of the reported incidence was occurred during the period from May to June.However,in most cases,another peak appeared from September to November.The trend of incidence was related to age,too.The overall trend of the reported incidence was a U-shape in north-south orientation and exposed an inverted U-shape in east-west.The correlation between the spatial distribution of HFMD was positive.Hunan,Guangxi and Guangdong were the hot areas,while the cold spots were Jilin,Inner Mongolia,Xinjiang,Gansu and Qinghai.
基金the National Natural Science Foundation of China(No.61872314,No.61802339)the Natural Science Foundation of Zhejiang Province(No.LY18F020024)+2 种基金the Humanities and Social Sciences Foundation of Ministry of Education in China(No.18YJC910017)the Major Humanities and Social Sciences Research Project in Zhejiang Province(2018QN021)the Open Project Program of the State Key Lab of CAD&CG of Zhejiang University(No.A2001)
文摘With the rapid development of Internet technology,a rich set of e-government data are collected by the government departments.For example,a variety of feedback text data can be obtained quickly and efficiently through various channels such as the mayor’s mailbox.It is an effective way to improve the working efficiency of the government to extract hot topics from large-scale e-government text data,establish the correlation between topics and geographic space,and interactively explore the sources of public feedback problems.However,it is a difficult task to explore the large-scale e-government text data with traditional visualization methods such as word cloud,because too many words are hardly distributed in a limited space which will largely disturb the visual perception.In this paper,we propose a visual analytics system for large-scale e-government data exploration by means of simplified word cloud.Firstly,a representation learning model is used to embed the text data into high-dimensional space to quantitatively represent the semantic structure features of e-government text data.Then,the high-dimensional vectors are projected into a two-dimensional space where the coordinate distribution of points effectively expresses the semantic similarity of original words,which also presents geographic features that can be quantized by means of a similarity computing model.In order to simplify the understanding of large-scale e-government data and improve the cognitive efficiency of word could,we adopt the adaptive blue noise method to sample the topic words,which can simplify the visual expression of word cloud and improve the understanding efficiency of e-government data without losing the semantic structure features.Furthermore,an abstraction and visual analysis system for large-scale e-government text data is designed and implemented by integrating the above representation learning model,sampling-based abstraction model of word cloud,and topic and geographic correlation analysis model.This system provides convenient human-computer interaction modes and supports users to explore the analysis and extraction of the characteristics hidden in large-scale e-government data.It also helps government departments quickly locate the hot topics of public concern and their related regional distribution,and provides decision support to further improve the work efficiency of the government.Case studies based on real-world datasets further verify the effectiveness and practicability of our system.
文摘It has been evidenced that peer review activities are positively correlated to scientists’bibliometric performance(e.g.,Ortega,2017,2019).However,how the number of paper’reviewing’interacts with a scientist’s’publishing’has not been addressed in previous studies.This paper attempts to employ the Granger causality inference to explore the directionality between a scientist’s publication performance and his/her review activities.Our dataset comprises scientists’reviewed articles derived from Publons in the Web of Knowledge database,and their publications retrieved from Pub Med.We find that scientists who reviewed less or published less tend to have Granger causality between reviewing and publishing activities.In addition,compared with early-career researchers,reviewing advances publishing for senior scientists.
基金supported by the Zhejiang Provincial Philosophy and Social Science Planning Project of China(Grant No.20NDJC096YB)the National Key Research and Development Project of China(Grant No.2017YFF0209600)
文摘The e-commerce standard internationalization has become the strategic targets of China’s digital economy.This paper proposes the system dynamics model through analyzing the internal and external factors of e-commerce standard internationalization under dynamic mechanism.The internationalization trend of China’s e-commerce standard is simulated by Vensim under adjusting economy factor,policy support factor,technical-innovation factor and industry supply chain’s service factor.The experiment results show that China’s international leadership on e-commerce and its influence on standard internationalization from the top-level design,strengthen industry supply chain’s standard certification and the technical-innovation of product standard factors,which can promote the high quality made-in-China brand.
基金Zhejiang Association of Postgraduate Education(No.2021-003)National Social Science Foundation of China(No.19ZDA348)Association of Fundamental Computing Education in Chinese Universities(No.2021-AFCEC-195)。
文摘In recent years,with the rapid development and expansion of postgraduate education in China,the cultivation quality has become increasingly prominent.In graduate education activities,there are many factors that affect the quality of cultivation,among which the tutor’s guiding ability is undoubtedly the key factor that affects the quality of graduate students’cultivation.In the 2020 National Graduate Education Conference,one of its topics is how to objectively quantify the guiding ability of supervisors based on which the teaching resources can be optimally allocated.Taking Hangzhou Dianzi University as an example,this paper investigates the index systems to evaluate the guiding ability of graduate students’supervisors including 6 first-level indicators and 19 second-level indicators in order to further improve the cultivation performance of graduate students.
