Pub Date : 2023-05-06DOI: 10.1177/01655515231169953
Tingting Li, Ziming Zeng, Shouqiang Sun, Jingjing Sun, Qingqing Li
This article aims to discover key users in public health emergencies and explore their public opinion evolution patterns, thus providing theoretical support for the establishment of a clear cyberspace. In this article, a multi-layer heterogeneous network model based on multiple node attributes (user nodes, microblogs nodes, emotional nodes and topic nodes) is constructed at each stage of the public opinion cycle. Specifically, a novel semi-supervised self-training method based on the bidirectional encoder representations from transformers (SSST-BERT) method is proposed to automatically label the fine-grained emotional nodes. The latent Dirichlet allocation (LDA) model is used to construct the topic nodes. Moreover, the degree centrality, betweenness centrality and closeness centrality of the constructed heterogeneous network are adopted to dynamically identify key users. Finally, the emotional states and topic tendencies of key users are explored to obtain the public opinion evolution pattern of emergencies. The experimental results show that the SSST-BERT automatically labels emotion categories with an F1-score of 80.48%. The key users identified by the constructed heterogeneous network are more representative of the opinion status of ordinary users. Analysis of the public opinion status of key users reveals that netizens show more negative emotions such as anger and fear in public health emergencies, and the shift of focus drives the evolution of discussion topics.
{"title":"Constructing a multi-layer heterogeneous networks model to explore the public opinion evolution pattern of key users in public health emergencies","authors":"Tingting Li, Ziming Zeng, Shouqiang Sun, Jingjing Sun, Qingqing Li","doi":"10.1177/01655515231169953","DOIUrl":"https://doi.org/10.1177/01655515231169953","url":null,"abstract":"This article aims to discover key users in public health emergencies and explore their public opinion evolution patterns, thus providing theoretical support for the establishment of a clear cyberspace. In this article, a multi-layer heterogeneous network model based on multiple node attributes (user nodes, microblogs nodes, emotional nodes and topic nodes) is constructed at each stage of the public opinion cycle. Specifically, a novel semi-supervised self-training method based on the bidirectional encoder representations from transformers (SSST-BERT) method is proposed to automatically label the fine-grained emotional nodes. The latent Dirichlet allocation (LDA) model is used to construct the topic nodes. Moreover, the degree centrality, betweenness centrality and closeness centrality of the constructed heterogeneous network are adopted to dynamically identify key users. Finally, the emotional states and topic tendencies of key users are explored to obtain the public opinion evolution pattern of emergencies. The experimental results show that the SSST-BERT automatically labels emotion categories with an F1-score of 80.48%. The key users identified by the constructed heterogeneous network are more representative of the opinion status of ordinary users. Analysis of the public opinion status of key users reveals that netizens show more negative emotions such as anger and fear in public health emergencies, and the shift of focus drives the evolution of discussion topics.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42342461","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 : 2023-05-06DOI: 10.1177/01655515231161562
C. Brys, Ismael Navas-Delgado, J. F. Aldana-Montes, M. D. M. Roldán-García
E-government services are subject to a growing level of complexity, which requires a disruptive approach that better support the citizen needs concerning the government administration. Nowadays, available information technologies facilitate the description and online execution of administrative tasks, saving time and reducing possible errors. These technologies reduce administrative costs but require a complex electronic government system. We propose using semantic technologies to describe the e-government organisational units and services in the Open Government Data and Services context. The use of semantics improves government management, service delivery and decision-making processes. This article presents an extension of related work, introducing the evolution of the Ontology for Electronic Government (EGO): integrating other existing ontologies, supporting new features to describe e-government services and widening the usage scenarios. This extension enables the use in a real scenario with four use cases: the electronic government in the Province of Misiones (Argentina). However, the use in the domain of electronic government in a provincial context is also a proof of concept that this approach is general enough to expand into superior domains of countries that adopt the republican system of government with the division of government into the executive, legislative and judicial branches.
{"title":"LEGO: Linked electronic government ontology","authors":"C. Brys, Ismael Navas-Delgado, J. F. Aldana-Montes, M. D. M. Roldán-García","doi":"10.1177/01655515231161562","DOIUrl":"https://doi.org/10.1177/01655515231161562","url":null,"abstract":"E-government services are subject to a growing level of complexity, which requires a disruptive approach that better support the citizen needs concerning the government administration. Nowadays, available information technologies facilitate the description and online execution of administrative tasks, saving time and reducing possible errors. These technologies reduce administrative costs but require a complex electronic government system. We propose using semantic technologies to describe the e-government organisational units and services in the Open Government Data and Services context. The use of semantics improves government management, service delivery and decision-making processes. This article presents an extension of related work, introducing the evolution of the Ontology for Electronic Government (EGO): integrating other existing ontologies, supporting new features to describe e-government services and widening the usage scenarios. This extension enables the use in a real scenario with four use cases: the electronic government in the Province of Misiones (Argentina). However, the use in the domain of electronic government in a provincial context is also a proof of concept that this approach is general enough to expand into superior domains of countries that adopt the republican system of government with the division of government into the executive, legislative and judicial branches.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47664568","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 : 2023-05-05DOI: 10.1177/01655515231169961
Yijin Chen, Hanming Lin, Jin Zhang, Yiming Zhao
This study aims to investigate consumers’ modification of retrieval platform switch paths across health-related search tasks and learning characteristics via such a switch. Mixed research methods were used in this study. A lab user experiment was designed to obtain data on consumers’ health information search behaviour. Screen recordings and interview data were both coded and analysed. Research results show that health consumers acquired different kinds of health knowledge units from different retrieval platforms, and there are five change patterns of retrieval platform switch paths which reveal three types of learning. The results suggest that health consumers learn not only task-related knowledge but also retrieval skills during the switch of retrieval platforms. The research findings further develop the search as learning process research framework from the dimension of retrieval platform switch patterns and contribute to the enhancement of consumers’ health information retrieval abilities.
{"title":"Online health information consumers’ learning across health-related search tasks from the perspective of retrieval platform switching","authors":"Yijin Chen, Hanming Lin, Jin Zhang, Yiming Zhao","doi":"10.1177/01655515231169961","DOIUrl":"https://doi.org/10.1177/01655515231169961","url":null,"abstract":"This study aims to investigate consumers’ modification of retrieval platform switch paths across health-related search tasks and learning characteristics via such a switch. Mixed research methods were used in this study. A lab user experiment was designed to obtain data on consumers’ health information search behaviour. Screen recordings and interview data were both coded and analysed. Research results show that health consumers acquired different kinds of health knowledge units from different retrieval platforms, and there are five change patterns of retrieval platform switch paths which reveal three types of learning. The results suggest that health consumers learn not only task-related knowledge but also retrieval skills during the switch of retrieval platforms. The research findings further develop the search as learning process research framework from the dimension of retrieval platform switch patterns and contribute to the enhancement of consumers’ health information retrieval abilities.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43791370","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 : 2023-05-02DOI: 10.1177/01655515231171088
A. Matysek
Individual interviews are not commonly used in library and information science (LIS). A content analysis of research papers published between 2015 and 2020 in seven journals yielded 323 articles applying interviews. Selected papers, extracted from the Scopus database, were examined qualitatively and quantitatively to find the description of the type of interview, the use of additional research methods, the number of interviewees and the topics of the studies. Interviews appeared in 11% of the research papers, confirming previous studies. They are often combined with other methods, in particular surveys and observations. Half of the interviews were conducted with up to 15 participants. Individual interviews were used most frequently in studies of information behaviour (19% of the papers), librarians, information retrieval and web search. This study contributes to better understanding interviews as a LIS research method and may facilitate the planning of research projects.
{"title":"The use of one-on-one interviews in library and information science: A scoping review","authors":"A. Matysek","doi":"10.1177/01655515231171088","DOIUrl":"https://doi.org/10.1177/01655515231171088","url":null,"abstract":"Individual interviews are not commonly used in library and information science (LIS). A content analysis of research papers published between 2015 and 2020 in seven journals yielded 323 articles applying interviews. Selected papers, extracted from the Scopus database, were examined qualitatively and quantitatively to find the description of the type of interview, the use of additional research methods, the number of interviewees and the topics of the studies. Interviews appeared in 11% of the research papers, confirming previous studies. They are often combined with other methods, in particular surveys and observations. Half of the interviews were conducted with up to 15 participants. Individual interviews were used most frequently in studies of information behaviour (19% of the papers), librarians, information retrieval and web search. This study contributes to better understanding interviews as a LIS research method and may facilitate the planning of research projects.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45774009","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 : 2023-05-02DOI: 10.1177/01655515231165230
I. Sharma, Abhay Sharma, Rekha Chaturvedi, Jitendra Rajpurohit, M. Kumar
Text clustering has been an overlooked field of text mining that requires more attention. Several applications require automatic text organisation which relies on an information retrieval system based on organised search results. Spherical k-means is a successful adaptation of the classic k-means algorithm for text clustering. However, conventional methods to accelerate k-means may not apply to spherical k-means due to the different nature of text document data. The proposed work introduces an iterative feature filtering technique that reduces the data size during the process of clustering which further produces more feature-relevant clusters in less time compared to classic spherical k-means. The novelty of the proposed method is that feature assessment is distinct from the objective function of clustering and derived from the cluster structure. Experimental results show that the proposed scheme achieves computation speed without sacrificing cluster quality over popular text corpora. The demonstrated results are satisfactory and outperform compared to recent works in this domain.
{"title":"SKIFF: Spherical K-means with iterative feature filtering for text document clustering","authors":"I. Sharma, Abhay Sharma, Rekha Chaturvedi, Jitendra Rajpurohit, M. Kumar","doi":"10.1177/01655515231165230","DOIUrl":"https://doi.org/10.1177/01655515231165230","url":null,"abstract":"Text clustering has been an overlooked field of text mining that requires more attention. Several applications require automatic text organisation which relies on an information retrieval system based on organised search results. Spherical k-means is a successful adaptation of the classic k-means algorithm for text clustering. However, conventional methods to accelerate k-means may not apply to spherical k-means due to the different nature of text document data. The proposed work introduces an iterative feature filtering technique that reduces the data size during the process of clustering which further produces more feature-relevant clusters in less time compared to classic spherical k-means. The novelty of the proposed method is that feature assessment is distinct from the objective function of clustering and derived from the cluster structure. Experimental results show that the proposed scheme achieves computation speed without sacrificing cluster quality over popular text corpora. The demonstrated results are satisfactory and outperform compared to recent works in this domain.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41979112","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 : 2023-04-26DOI: 10.1177/01655515231165228
Na Wei, Songzheng Zhao, J. Liu, Shenghui Wang
Social media provides customers with great opportunities to share their opinions regarding certain products and services. Comparative text, as an important expression form, deserves further exploration, since it contains considerable comparative information between different products and services. In this study, we review existing research on Comparative Text Mining (CTM) in the past 16 years. Basic concepts related to CTM are first described, and a general research framework is subsequently proposed. We then dive into each component of the research framework, ranging from data acquisition, comparative text identification (CTI), comparative relation extraction (CRE), to potential applications. In addition, we conduct extensive experimental analysis on existing methods for CTI and CRE, and clarify their limitations. Accordingly, we provide corresponding insights, and point out future research directions.
{"title":"A review for comparative text mining: From data acquisition to practical application","authors":"Na Wei, Songzheng Zhao, J. Liu, Shenghui Wang","doi":"10.1177/01655515231165228","DOIUrl":"https://doi.org/10.1177/01655515231165228","url":null,"abstract":"Social media provides customers with great opportunities to share their opinions regarding certain products and services. Comparative text, as an important expression form, deserves further exploration, since it contains considerable comparative information between different products and services. In this study, we review existing research on Comparative Text Mining (CTM) in the past 16 years. Basic concepts related to CTM are first described, and a general research framework is subsequently proposed. We then dive into each component of the research framework, ranging from data acquisition, comparative text identification (CTI), comparative relation extraction (CRE), to potential applications. In addition, we conduct extensive experimental analysis on existing methods for CTI and CRE, and clarify their limitations. Accordingly, we provide corresponding insights, and point out future research directions.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48306350","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 : 2023-04-24DOI: 10.1177/01655515231167293
Wiem Chebil, L. Soualmia
To improve the performance of information retrieval systems (IRSs), we propose in this article a novel approach that enriches the user’s queries with new concepts. Indeed, query expansion is one of the best methods that plays an important role in improving searches for a better semantic information retrieval. The proposed approach in this study combines possibilistic networks (PNs), the vector space model (VSM) and pseudo-relevance feedback (PRF) to evaluate and add relevant concepts to the initial index of the user’s query. First, query expansion is performed using PN, VSM and domain knowledge. PRF is then exploited to enrich, in a second round, the user’s query by applying the same approach used in the first expansion step. To evaluate the performance of the developed system, denoted conceptual information retrieval model (CIRM), several experiments of query expansion are performed. The experiments carried out on the OHSUMED and Clinical Trials corpora showed that using the two measures of possibility and necessity combined the cosinus similarity and PRF improves the query expansion process. Indeed, the improvement rate of our approach compared with the baseline is +28, 49% in terms of P@5.
{"title":"Improving semantic information retrieval by combining possibilistic networks, vector space model and pseudo-relevance feedback","authors":"Wiem Chebil, L. Soualmia","doi":"10.1177/01655515231167293","DOIUrl":"https://doi.org/10.1177/01655515231167293","url":null,"abstract":"To improve the performance of information retrieval systems (IRSs), we propose in this article a novel approach that enriches the user’s queries with new concepts. Indeed, query expansion is one of the best methods that plays an important role in improving searches for a better semantic information retrieval. The proposed approach in this study combines possibilistic networks (PNs), the vector space model (VSM) and pseudo-relevance feedback (PRF) to evaluate and add relevant concepts to the initial index of the user’s query. First, query expansion is performed using PN, VSM and domain knowledge. PRF is then exploited to enrich, in a second round, the user’s query by applying the same approach used in the first expansion step. To evaluate the performance of the developed system, denoted conceptual information retrieval model (CIRM), several experiments of query expansion are performed. The experiments carried out on the OHSUMED and Clinical Trials corpora showed that using the two measures of possibility and necessity combined the cosinus similarity and PRF improves the query expansion process. Indeed, the improvement rate of our approach compared with the baseline is +28, 49% in terms of P@5.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47951954","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 : 2023-04-24DOI: 10.1177/01655515231169949
Sijing Chen, Lu Xiao
Persuasion aims at affecting the audience’s attitude and behaviour through a series of messages containing persuasion strategies. In the context of misinformation spread, identifying the persuasion strategies is important in order to warn people to be aware of the analogous persuasion attempts in the future. In this work, we address the prediction of persuasion strategies in micro-blogging posts through a multi-label classification approach based on a variety of lexical and semantic features. We conduct our experiments using a set of well-known multi-label classification algorithms, including multi-label decision tree, multi-label k-nearest neighbours, multi-label random forest, binary relevance and classifier chains. The results show that the model incorporating classifier chains and XGBoost algorithm achieves the best subset accuracy of 0.779 and the highest macro F1-score of 0.847. In addition, we evaluated and compared the features’ importance for different persuasion strategies and analysed the major errors of miss-out prediction. The findings of this article provide a benchmark for the multi-label classification of persuasion strategies in micro-blogging posts and lead to a better understanding of different persuasion attempts contained in social media misinformation.
{"title":"Predicting and characterising persuasion strategies in misinformation content over social media based on the multi-label classification approach","authors":"Sijing Chen, Lu Xiao","doi":"10.1177/01655515231169949","DOIUrl":"https://doi.org/10.1177/01655515231169949","url":null,"abstract":"Persuasion aims at affecting the audience’s attitude and behaviour through a series of messages containing persuasion strategies. In the context of misinformation spread, identifying the persuasion strategies is important in order to warn people to be aware of the analogous persuasion attempts in the future. In this work, we address the prediction of persuasion strategies in micro-blogging posts through a multi-label classification approach based on a variety of lexical and semantic features. We conduct our experiments using a set of well-known multi-label classification algorithms, including multi-label decision tree, multi-label k-nearest neighbours, multi-label random forest, binary relevance and classifier chains. The results show that the model incorporating classifier chains and XGBoost algorithm achieves the best subset accuracy of 0.779 and the highest macro F1-score of 0.847. In addition, we evaluated and compared the features’ importance for different persuasion strategies and analysed the major errors of miss-out prediction. The findings of this article provide a benchmark for the multi-label classification of persuasion strategies in micro-blogging posts and lead to a better understanding of different persuasion attempts contained in social media misinformation.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47004905","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 : 2023-04-21DOI: 10.1177/01655515231167384
Deborah Lee
This article analyses the classification of musical forms in Western art music. It examines how some sources in the music domain classify musical forms, and the categorisations and complexities inherent within these classifications. It analyses the table of contents from music domain textbooks, treating them as knowledge organisation systems, as well as analysing music domain descriptions of the knowledge organisation of forms. Form is found to be a complicated type of information, with an intriguing relationship to genre. The analysis of domain classifications reveals five key categorisations: texture, sectionalisation, size of structure, definable-ness and medium. Various complexities about form are elicited, such as form-as-process, complicated whole-part form relationships, an interesting spectrum of definable-ness, and the dependency of form on medium and texture. This article examines a rarely discussed type of information, form, and its approach could be usefully extended to other subjects.
{"title":"Organising music’s structures: The classification of musical forms in Western art music","authors":"Deborah Lee","doi":"10.1177/01655515231167384","DOIUrl":"https://doi.org/10.1177/01655515231167384","url":null,"abstract":"This article analyses the classification of musical forms in Western art music. It examines how some sources in the music domain classify musical forms, and the categorisations and complexities inherent within these classifications. It analyses the table of contents from music domain textbooks, treating them as knowledge organisation systems, as well as analysing music domain descriptions of the knowledge organisation of forms. Form is found to be a complicated type of information, with an intriguing relationship to genre. The analysis of domain classifications reveals five key categorisations: texture, sectionalisation, size of structure, definable-ness and medium. Various complexities about form are elicited, such as form-as-process, complicated whole-part form relationships, an interesting spectrum of definable-ness, and the dependency of form on medium and texture. This article examines a rarely discussed type of information, form, and its approach could be usefully extended to other subjects.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49110379","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 : 2023-04-18DOI: 10.1177/01655515231167388
Dejian Yu, Zhao Yan
In the era of the Internet and big data, the PageRank (PR) algorithm is a constantly evolving research field. However, there is no systematic research to explore the overall development trend of the PR domain. This article evaluates 1446 articles related to the PR algorithm and provides a thorough understanding of the PR field through the main path analysis (MPA). Through two basic main paths, a number of papers that play a leading role have been identified, which outline the backbone of the PR domain. Based on the analysis of multiple main paths, four main subareas have been investigated. There are accelerating the computation of PR, comprehensive applications of PR, researches on academic impact assessment and age preference in network evolution. Finally, this article discusses the research findings and the future directions of the PR field. It is the first attempt to identify the development trend of the PR domain through MPA, thus providing an insight into the knowledge evolution of the PR field over the past two decades.
{"title":"Knowledge diffusion trajectories of PageRank: A main path analysis","authors":"Dejian Yu, Zhao Yan","doi":"10.1177/01655515231167388","DOIUrl":"https://doi.org/10.1177/01655515231167388","url":null,"abstract":"In the era of the Internet and big data, the PageRank (PR) algorithm is a constantly evolving research field. However, there is no systematic research to explore the overall development trend of the PR domain. This article evaluates 1446 articles related to the PR algorithm and provides a thorough understanding of the PR field through the main path analysis (MPA). Through two basic main paths, a number of papers that play a leading role have been identified, which outline the backbone of the PR domain. Based on the analysis of multiple main paths, four main subareas have been investigated. There are accelerating the computation of PR, comprehensive applications of PR, researches on academic impact assessment and age preference in network evolution. Finally, this article discusses the research findings and the future directions of the PR field. It is the first attempt to identify the development trend of the PR domain through MPA, thus providing an insight into the knowledge evolution of the PR field over the past two decades.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42514864","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：