Pub Date : 2023-09-10DOI: 10.1177/01655515231191226
Faten Hamad
COVID-19 has changed the information landscape. The results were the wide spread of information of all kinds and from all sources, leading to increased information disorder (i.e. disinformation, misinformation practices). This study aimed to explore the practices of academic libraries during times of crisis from the staff perception in four public universities in Jordan to correct the information disorder and hence create information resilience among community members. Exploring these practices helps shed light on the libraries’ contribution to creating information resilience practices and hence an information-resilient community. An interview was used to collect deep insights from 26 library staff working in the Information Division at the four academic libraries. The results were mainly directed towards the importance of increasing community awareness and providing access to quality information sources. It also affirmed the importance of information skills to help individuals locate the right and accurate information. It was affirmed that developing and promoting information literacy programmes was the main pillar to countering information disorder and establishing information resilience. The findings will provide insights for other academic libraries on the best practices to create a information resilient community.
{"title":"Libraries roles and practices to enhance information resilience: Academic librarians’ perspectives","authors":"Faten Hamad","doi":"10.1177/01655515231191226","DOIUrl":"https://doi.org/10.1177/01655515231191226","url":null,"abstract":"COVID-19 has changed the information landscape. The results were the wide spread of information of all kinds and from all sources, leading to increased information disorder (i.e. disinformation, misinformation practices). This study aimed to explore the practices of academic libraries during times of crisis from the staff perception in four public universities in Jordan to correct the information disorder and hence create information resilience among community members. Exploring these practices helps shed light on the libraries’ contribution to creating information resilience practices and hence an information-resilient community. An interview was used to collect deep insights from 26 library staff working in the Information Division at the four academic libraries. The results were mainly directed towards the importance of increasing community awareness and providing access to quality information sources. It also affirmed the importance of information skills to help individuals locate the right and accurate information. It was affirmed that developing and promoting information literacy programmes was the main pillar to countering information disorder and establishing information resilience. The findings will provide insights for other academic libraries on the best practices to create a information resilient community.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"366 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136073451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.1177/01655515231193851
Lili Shang, Meiyun Zuo
In aspect-based sentiment analysis, a fundamental task is extracting aspect terms from opinionated sentences. Aspect term extraction (ATE) has been found to play a critical role among several scenarios, such as service quality improvement and recommendation systems. While deep learning-based methods have achieved great progress in ATE, they mainly consider sequential semantic information and generally ignore the utilisation of syntactic relations of the whole sentence on overall meanings. Furthermore, performances of these methods may also be diminished by poor handling of relation and text noises. To address these issues, we propose a fused sequential and hierarchical representation (FSHR) model, wherein both sequential and hierarchical representations are generated, which facilitates not only the capture of linear semantic information for predicting meaning-related aspect terms but also the utilisation of syntactic relations over the entire sentence to better identify structure-related aspect terms. Moreover, to refine the aspect representation, we incorporate relation-gate mechanism which selectively activates meaningful syntactic dependency paths and design the multi-way aspect attention which prompts the model to focus on relevant text segments about particular aspects. Eventually, sequential and hierarchical representations are adaptively fused for aspect prediction. Experiment results on four datasets demonstrate that FSHR outperforms competitive baselines, and further extensive analyses reveal the effectiveness of our model.
{"title":"Aspect term extraction via adaptive fusion of sequential and hierarchical representation","authors":"Lili Shang, Meiyun Zuo","doi":"10.1177/01655515231193851","DOIUrl":"https://doi.org/10.1177/01655515231193851","url":null,"abstract":"In aspect-based sentiment analysis, a fundamental task is extracting aspect terms from opinionated sentences. Aspect term extraction (ATE) has been found to play a critical role among several scenarios, such as service quality improvement and recommendation systems. While deep learning-based methods have achieved great progress in ATE, they mainly consider sequential semantic information and generally ignore the utilisation of syntactic relations of the whole sentence on overall meanings. Furthermore, performances of these methods may also be diminished by poor handling of relation and text noises. To address these issues, we propose a fused sequential and hierarchical representation (FSHR) model, wherein both sequential and hierarchical representations are generated, which facilitates not only the capture of linear semantic information for predicting meaning-related aspect terms but also the utilisation of syntactic relations over the entire sentence to better identify structure-related aspect terms. Moreover, to refine the aspect representation, we incorporate relation-gate mechanism which selectively activates meaningful syntactic dependency paths and design the multi-way aspect attention which prompts the model to focus on relevant text segments about particular aspects. Eventually, sequential and hierarchical representations are adaptively fused for aspect prediction. Experiment results on four datasets demonstrate that FSHR outperforms competitive baselines, and further extensive analyses reveal the effectiveness of our model.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47860769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quick development of mobile network and smart devices provides a convenience way for information sharing in online social networks, which also accelerates the propagation of harmful information, thus how to select the hidden influential nodes with lower management cost for reducing the propagation speed of harmful information is an important task. In this article, we propose a greedy hidden influential node selection algorithm based on the epidemic model and cost–benefit analysis. First, we investigate the user behaviour dynamic characteristics from two perspectives of social relationships and interaction behaviours, and then susceptible and infected (SI) epidemic model is applied and user influence is estimated. Second, considering the management cost and benefit of different users, a greedy hidden influential node selection algorithm based on the cost–benefit analysis is proposed. Finally, a series of experiments are conducted using the public social network data set and the data set collected from Sina Weibo, to verify the performance and practicality of the developed method. The experimental results demonstrate that our method outperforms other related methods in harmful information propagation control.
{"title":"Hidden influential node selection based on cost–benefit analysis for harmful information propagation control","authors":"Zhaoli Liu, Qindong Sun, Shancang Li, Zhihai Yang, Beibei Zhang","doi":"10.1177/01655515231193853","DOIUrl":"https://doi.org/10.1177/01655515231193853","url":null,"abstract":"The quick development of mobile network and smart devices provides a convenience way for information sharing in online social networks, which also accelerates the propagation of harmful information, thus how to select the hidden influential nodes with lower management cost for reducing the propagation speed of harmful information is an important task. In this article, we propose a greedy hidden influential node selection algorithm based on the epidemic model and cost–benefit analysis. First, we investigate the user behaviour dynamic characteristics from two perspectives of social relationships and interaction behaviours, and then susceptible and infected (SI) epidemic model is applied and user influence is estimated. Second, considering the management cost and benefit of different users, a greedy hidden influential node selection algorithm based on the cost–benefit analysis is proposed. Finally, a series of experiments are conducted using the public social network data set and the data set collected from Sina Weibo, to verify the performance and practicality of the developed method. The experimental results demonstrate that our method outperforms other related methods in harmful information propagation control.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47308434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.1177/01655515231193847
Muhaimin Karim, Gunilla Widén
The article presents findings from a study that examined how young people select, consult and evaluate multiple information sources to validate the information they seek. It contributes to the field of information behaviour and helps in designing better information services. Eight focus group interviews were carried out in four different locations across Europe. A total of 37 young people participated through purposive sampling. The study illustrates participants’ complex information pathways through which they consult multiple sources to reach the most trusted information source. The content analysis of the data showed that ascribed cognitive authority and affective factors such as confidentiality, privacy and empathy strongly determine the selection of an information source. The study observes the young participants’ dependency on networked and human sources for ease of access and reluctance to rely on mainstream media and textual information. The study has strong practical implications for designing information services and developing communication materials targeted at young people.
{"title":"Strategies for information source selection: A focus group study on young people in Europe","authors":"Muhaimin Karim, Gunilla Widén","doi":"10.1177/01655515231193847","DOIUrl":"https://doi.org/10.1177/01655515231193847","url":null,"abstract":"The article presents findings from a study that examined how young people select, consult and evaluate multiple information sources to validate the information they seek. It contributes to the field of information behaviour and helps in designing better information services. Eight focus group interviews were carried out in four different locations across Europe. A total of 37 young people participated through purposive sampling. The study illustrates participants’ complex information pathways through which they consult multiple sources to reach the most trusted information source. The content analysis of the data showed that ascribed cognitive authority and affective factors such as confidentiality, privacy and empathy strongly determine the selection of an information source. The study observes the young participants’ dependency on networked and human sources for ease of access and reluctance to rely on mainstream media and textual information. The study has strong practical implications for designing information services and developing communication materials targeted at young people.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49239381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-06DOI: 10.1177/01655515231191221
Luís Madureira, Aleš Popovič, Mauro Castelli
The competitive intelligence (CI) construct must be scientifically defined, characterised, empirically validated and accurately measured to grow in science and business. This study aims at elevating the accuracy of the empirical validation of the CI construct suggested and confirmed by Madureira, Popovic and Castelli to serve as the scientific foundation for CI praxis. This construct is selected due to its unmatched recency, thoroughness, universality identified limitations of its empirical validation. We relied on a multistrand design of fully sequential with equivalent status qualitative and quantitative mix-methods followed by the triangulation of the findings and the development of the meta-inferences. Validity, reliability and applicability were tested using computer-aided text analysis and artificial intelligence methods based on 61 in-depth interviews with CI subject matter experts. Contributions to knowledge advancement and relevance to practice derive from the scientific-grade empirical construct validation, providing undisputed levels of accuracy, consistency, applicability, and triangulation of results. This study highlights three critical implications. First, the delimitation of the body of knowledge and recognition of the CI domain serve as the baseline for theory development. Second, the validated construct guarantees reproducibility, replicability and generalisability, laying the foundations for establishing CI science, practice and education. Third, creating a common language and shared understanding will drive the much-claimed definitional consensus. This study thus stands as a foundational pillar in supporting CI praxis in improving decision-making quality and the performance of organisations.
{"title":"Competitive intelligence empirical validation and application: Foundations for knowledge advancement and relevance to practice","authors":"Luís Madureira, Aleš Popovič, Mauro Castelli","doi":"10.1177/01655515231191221","DOIUrl":"https://doi.org/10.1177/01655515231191221","url":null,"abstract":"The competitive intelligence (CI) construct must be scientifically defined, characterised, empirically validated and accurately measured to grow in science and business. This study aims at elevating the accuracy of the empirical validation of the CI construct suggested and confirmed by Madureira, Popovic and Castelli to serve as the scientific foundation for CI praxis. This construct is selected due to its unmatched recency, thoroughness, universality identified limitations of its empirical validation. We relied on a multistrand design of fully sequential with equivalent status qualitative and quantitative mix-methods followed by the triangulation of the findings and the development of the meta-inferences. Validity, reliability and applicability were tested using computer-aided text analysis and artificial intelligence methods based on 61 in-depth interviews with CI subject matter experts. Contributions to knowledge advancement and relevance to practice derive from the scientific-grade empirical construct validation, providing undisputed levels of accuracy, consistency, applicability, and triangulation of results. This study highlights three critical implications. First, the delimitation of the body of knowledge and recognition of the CI domain serve as the baseline for theory development. Second, the validated construct guarantees reproducibility, replicability and generalisability, laying the foundations for establishing CI science, practice and education. Third, creating a common language and shared understanding will drive the much-claimed definitional consensus. This study thus stands as a foundational pillar in supporting CI praxis in improving decision-making quality and the performance of organisations.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43429490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-23DOI: 10.1177/01655515231191231
Shengzhi Huang, Wei Lu, Yong Huang, Zhuoran Luo
Scholar performance evaluation is extremely important in research assessment decisions, such as funding allocation, academic rankings, and academic promotion. In this article, we propose the institution Q model (IQ) and its two variants (IQ-2 and IQ-3), which aim to evaluate the individual-level research ability to publish high-quality scientific papers. Specifically, our models integrate scientists’ institutions, countries and collaborators as valuable prior information and jointly evaluate the research ability of scientists from different institutions. To estimate model parameters and hidden variables defined in our models, we propose a generic BBVI-EM algorithm. To test the effectiveness of our models, we examine their performance on the synthetic data and the empirical data (17,750/26,992 scientists in the computer science/physics field). We find that our models can more accurately quantify the research ability of scientists and institutions and more effectively predict scientists’ scientific impact (the h-index and total citations) than the Q model and common machine learning models. In conclusion, our models are effective evaluation and prediction tools for quantifying research ability and predicting the scientific impact, and the BBVI-EM algorithm is an effective variational inference algorithm. This study makes a theoretical contribution to broaden the idea of incorporating the academic environment into scientific evaluation.
{"title":"Quantifying scientists’ research ability by taking institutions’ scientific impact as priori information","authors":"Shengzhi Huang, Wei Lu, Yong Huang, Zhuoran Luo","doi":"10.1177/01655515231191231","DOIUrl":"https://doi.org/10.1177/01655515231191231","url":null,"abstract":"Scholar performance evaluation is extremely important in research assessment decisions, such as funding allocation, academic rankings, and academic promotion. In this article, we propose the institution Q model (IQ) and its two variants (IQ-2 and IQ-3), which aim to evaluate the individual-level research ability to publish high-quality scientific papers. Specifically, our models integrate scientists’ institutions, countries and collaborators as valuable prior information and jointly evaluate the research ability of scientists from different institutions. To estimate model parameters and hidden variables defined in our models, we propose a generic BBVI-EM algorithm. To test the effectiveness of our models, we examine their performance on the synthetic data and the empirical data (17,750/26,992 scientists in the computer science/physics field). We find that our models can more accurately quantify the research ability of scientists and institutions and more effectively predict scientists’ scientific impact (the h-index and total citations) than the Q model and common machine learning models. In conclusion, our models are effective evaluation and prediction tools for quantifying research ability and predicting the scientific impact, and the BBVI-EM algorithm is an effective variational inference algorithm. This study makes a theoretical contribution to broaden the idea of incorporating the academic environment into scientific evaluation.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"61 24","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41312015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-21DOI: 10.1177/01655515231191233
Penghui Lyu, Xiuli Liu, Ting Yao
Bibliometrics research has been developed for many years and achieved a great many scientific achievements. The aim of this study is to understand the current research status and development directions of research on bibliometrics. This study implements bibliometric methods based on the Web of Science to analyse the publications, subjects, citation, co-citation, collaboration and keywords of bibliometrics from 1969 to 2022. Bibliometrics is now in the development phase from its cumulative publication curve and citation analysis. Information Science & Library Science and Computer Science are the two major subjects on bibliometric research. Garfield E has the most citations and co-citation frequency in the field of bibliometrics. The number of countries cooperating with the United States is the largest and China is the most productive country; Beijing, London and Madrid are the three sub-network centres of the city cooperation network; Zhang L owns the largest number of author collaborations. Research content on bibliometrics focuses mainly on bibliometrics theory, methods, research evaluation, techniques, tools and applications. The results in this study are beneficial to researchers and readers who are interested in the field of bibliometrics and other related fields to understand the overall picture of bibliometrics, which is conducive to the future development of bibliometrics.
文献计量学研究经过多年的发展，取得了许多科学成果。本研究旨在了解文献计量学研究的现状和发展方向。本研究采用基于Web of Science的文献计量学方法，对1969 - 2022年文献计量学的出版物、学科、被引、共被引、合作和关键词进行了分析。从文献计量学的累积发表曲线和引文分析来看，文献计量学目前正处于发展阶段。信息科学与图书馆学和计算机科学是文献计量学研究的两个主要学科。Garfield E是文献计量学领域中被引频次和共被引频次最多的论文。与美国合作的国家数量最多，中国是生产力最高的国家;北京、伦敦和马德里是城市合作网络的三个子网络中心;作者合作次数最多的是张l。文献计量学的研究内容主要集中在文献计量学的理论、方法、研究评价、技术、工具和应用等方面。本研究结果有利于对文献计量学及其他相关领域感兴趣的研究者和读者了解文献计量学的全貌，有利于文献计量学未来的发展。
{"title":"A bibliometric analysis of literature on bibliometrics in recent half-century","authors":"Penghui Lyu, Xiuli Liu, Ting Yao","doi":"10.1177/01655515231191233","DOIUrl":"https://doi.org/10.1177/01655515231191233","url":null,"abstract":"Bibliometrics research has been developed for many years and achieved a great many scientific achievements. The aim of this study is to understand the current research status and development directions of research on bibliometrics. This study implements bibliometric methods based on the Web of Science to analyse the publications, subjects, citation, co-citation, collaboration and keywords of bibliometrics from 1969 to 2022. Bibliometrics is now in the development phase from its cumulative publication curve and citation analysis. Information Science & Library Science and Computer Science are the two major subjects on bibliometric research. Garfield E has the most citations and co-citation frequency in the field of bibliometrics. The number of countries cooperating with the United States is the largest and China is the most productive country; Beijing, London and Madrid are the three sub-network centres of the city cooperation network; Zhang L owns the largest number of author collaborations. Research content on bibliometrics focuses mainly on bibliometrics theory, methods, research evaluation, techniques, tools and applications. The results in this study are beneficial to researchers and readers who are interested in the field of bibliometrics and other related fields to understand the overall picture of bibliometrics, which is conducive to the future development of bibliometrics.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44027748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-21DOI: 10.1177/01655515231191210
Meng Wang, Yuwen Hua, Ya Chen, Jing’an Qian, Lianfu Pang
With the continuous development of information technology, information literacy education is becoming more and more important for university students. However, information literacy education in Chinese universities is still in the development stage and the cultivation effect needs to be improved. Therefore, this study takes the teaching of Information Retrieval as an example, based on constructivist learning theory and social exchange theory, reveals the influential factors related to the cultivation effect and explores the causal rela-tionship between each variable and the cultivation effect through a qualitative comparative analysis research method with a configura-tion perspective. This study finds that university students in information literacy education can be classified into four categories: context-driven, class-guidance, meaning-realised and motivation satisfaction. For these four types of university students, this study proposes corresponding countermeasures for information literacy cultivation in order to enhance the effectiveness of cultivation.
{"title":"Factors affecting university students’ information literacy education: An empirical study using fuzzy-set qualitative comparative analysis","authors":"Meng Wang, Yuwen Hua, Ya Chen, Jing’an Qian, Lianfu Pang","doi":"10.1177/01655515231191210","DOIUrl":"https://doi.org/10.1177/01655515231191210","url":null,"abstract":"With the continuous development of information technology, information literacy education is becoming more and more important for university students. However, information literacy education in Chinese universities is still in the development stage and the cultivation effect needs to be improved. Therefore, this study takes the teaching of Information Retrieval as an example, based on constructivist learning theory and social exchange theory, reveals the influential factors related to the cultivation effect and explores the causal rela-tionship between each variable and the cultivation effect through a qualitative comparative analysis research method with a configura-tion perspective. This study finds that university students in information literacy education can be classified into four categories: context-driven, class-guidance, meaning-realised and motivation satisfaction. For these four types of university students, this study proposes corresponding countermeasures for information literacy cultivation in order to enhance the effectiveness of cultivation.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41748409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-21DOI: 10.1177/01655515231191351
Prashasti Singh, V. K. Singh, Rajesh Piryani
Scholarly databases are now being increasingly used for search and retrieval of research articles in different subject areas. Several previous studies have shown that different databases vary in their coverage of publication sources, and therefore, one may expect that for a given query, they may retrieve different results. However, how do these databases compare in terms of relevance of the retrieved results is relatively unexplored. This study, therefore, attempts to bridge this research gap by carrying out a systematic study of retrieval relevance of the three scholarly databases – Web of Science, Scopus and Dimensions. Five selected queries are used for this purpose. The retrieved results from the three databases for the given queries are first analysed in terms of volume of retrieved records, language of retrieved records, etc. Thereafter, a user-based annotation scheme is used to assess and compare the relevance of retrieved results. The standard measure of normalised discounted cumulative gain (NDCG) and Spearman rank correlation coefficient (SRCC) is computed for the purpose. Results indicate that although the number of retrieved results for the same query differs significantly in the three databases, the databases differ only marginally in retrieval relevance, with Web of Science having a slight edge over other two.
学术数据库现在越来越多地用于搜索和检索不同学科领域的研究论文。先前的一些研究表明，不同的数据库对出版物来源的覆盖范围各不相同，因此，对于给定的查询，它们可能会检索到不同的结果。然而，这些数据库在检索结果的相关性方面是如何比较的，这是相对未知的。因此，本研究试图通过对Web of Science、Scopus和Dimensions三个学术数据库的检索相关性进行系统研究来弥补这一研究缺口。为此选择了5个查询。首先根据检索记录的数量、检索记录的语言等对三个数据库中给定查询的检索结果进行分析。然后，使用基于用户的注释方案来评估和比较检索结果的相关性。为此，计算了标准化贴现累积增益(NDCG)和斯皮尔曼等级相关系数(SRCC)的标准度量。结果表明，虽然同一查询的检索结果数量在三个数据库中差异很大，但检索相关性差异很小，其中Web of Science比其他两个数据库稍微有优势。
{"title":"Scholarly article retrieval from Web of Science, Scopus and Dimensions: A comparative analysis of retrieval quality","authors":"Prashasti Singh, V. K. Singh, Rajesh Piryani","doi":"10.1177/01655515231191351","DOIUrl":"https://doi.org/10.1177/01655515231191351","url":null,"abstract":"Scholarly databases are now being increasingly used for search and retrieval of research articles in different subject areas. Several previous studies have shown that different databases vary in their coverage of publication sources, and therefore, one may expect that for a given query, they may retrieve different results. However, how do these databases compare in terms of relevance of the retrieved results is relatively unexplored. This study, therefore, attempts to bridge this research gap by carrying out a systematic study of retrieval relevance of the three scholarly databases – Web of Science, Scopus and Dimensions. Five selected queries are used for this purpose. The retrieved results from the three databases for the given queries are first analysed in terms of volume of retrieved records, language of retrieved records, etc. Thereafter, a user-based annotation scheme is used to assess and compare the relevance of retrieved results. The standard measure of normalised discounted cumulative gain (NDCG) and Spearman rank correlation coefficient (SRCC) is computed for the purpose. Results indicate that although the number of retrieved results for the same query differs significantly in the three databases, the databases differ only marginally in retrieval relevance, with Web of Science having a slight edge over other two.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43469689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1177/01655515231191213
Zhuoran Luo, Jiangen He, J. Qian, Yuqi Wang, Wei Lu
Influential scientific papers tend to be primarily based on combinations of prior works. However, assessing the potential impact of a new scientific paper remains a challenging task. In this article, we introduce an innovative framework to investigate the relationship between the embedding of citation networks and a paper’s future citation counts, based on the graph representation learning approach. First, we employ three Nobel Prize-winning topic papers from the Web of Science as our data source. Through data preprocessing and direct citation network modelling, we train the struc2vec model to obtain embeddings of papers’ citation network structure. Then, we perform visualisation and analysis on two types of networks. One is the direct-citation network, in which we identify four patterns of linkage between newly published papers and existing knowledge, and the other is the co-citation network, where we measure three structural variation indicators of new papers based on existing research findings. Finally, a statistical test is used to examine the predictive potentials of network embeddings. The results demonstrate that the structural features captured by the graph representation learning model can be used to predict a paper’s citation counts and impact. This article innovatively combines cluster analysis, visual analysis and statistical analysis to gain insights into the relationship between the hard-to-explain structural embeddings of newly published papers in a citation network and their future citations.
有影响力的科学论文往往主要是基于前人工作的结合。然而，评估一篇新的科学论文的潜在影响仍然是一项具有挑战性的任务。在本文中，我们引入了一个创新的框架，基于图表示学习方法来研究引文网络嵌入与论文未来被引次数之间的关系。首先，我们使用来自Web of Science的三篇诺贝尔奖获奖主题论文作为我们的数据源。通过数据预处理和直接引文网络建模，对struc2vec模型进行训练，得到论文引文网络结构的嵌入。然后，我们对两种类型的网络进行可视化和分析。一种是直接引用网络，我们在其中确定了新发表论文与现有知识之间的四种联系模式;另一种是共被引网络，我们在现有研究成果的基础上测量了新发表论文的三个结构变化指标。最后，使用统计检验来检验网络嵌入的预测潜力。结果表明，图表示学习模型捕获的结构特征可以用于预测论文的被引次数和影响力。本文创新性地结合了聚类分析、可视化分析和统计分析，以深入了解引文网络中新发表论文中难以解释的结构嵌入与其未来被引之间的关系。
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