Pub Date : 2023-10-23DOI: 10.1108/lht-02-2023-0063
Rongying Zhao, Weijie Zhu, He Huang, Wenxin Chen
Purpose Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications. Design/methodology/approach This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns. Findings The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication. Originality/value Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.
{"title":"Social mediametrics: the mention laws and patterns of scientific literature","authors":"Rongying Zhao, Weijie Zhu, He Huang, Wenxin Chen","doi":"10.1108/lht-02-2023-0063","DOIUrl":"https://doi.org/10.1108/lht-02-2023-0063","url":null,"abstract":"Purpose Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications. Design/methodology/approach This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns. Findings The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication. Originality/value Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":"30 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135366133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.1108/lht-10-2022-0473
Chien-Wen Shen, Phung Phi Tran
Purpose This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified. Design/methodology/approach To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures. Findings The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries. Research limitations/implications Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers. Originality/value This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.
本研究旨在通过将多种方法与不同的数据源(如学术论文和新闻文章)相结合,提供区块链发展的更完整图景。本研究通过对收集数据中提取的高频关键词进行分析,根据每个主题聚类之间的相互关系来展示每个主题的发展状况。此外,应用上述方法将有助于了解热门研究课题、作者、地点、机构和国家。确定了区块链研究与新技术的差异。为了识别和发现区块链发展联系,研究人员使用了共现、书目耦合、共引和合著等搜索术语来帮助我们了解顶级研究主题、作者、地点、机构和国家。本研究还使用文本挖掘分析来识别区块链文章的主要概念和语义结构。这些发现显示了基于每个主题集群的链接的基本主题。“技术”、“交易”、“隐私与安全”、“环境”和“共识”在研究中与区块链联系最为密切,而“平台”、“大数据与云”、“网络”、“医疗与商业”和“认证”与区块链新闻联系最为密切。本文将区块链原则分为五种模式:硬件和基础设施、数据、网络、应用和共识。这些统计数据有助于作者了解顶级研究课题、作者、地点、出版机构和国家。由于使用了Web of Science (WoS)和LexisNexis的学术数据,因此本研究的来源很少。其他人则建议合并国外的数据集。WoS是世界上最大和最常用的科学论文评估数据库之一。这项研究有几个用途和好处。首先,关键概念的发现可以帮助学者了解区块链研究趋势,以便他们可以优先考虑研究计划。第二,书目耦合链接区块链学术论文。它帮助信息搜寻者搜索和分类材料。共引分析结果可以帮助研究人员识别潜在的合作伙伴和各自领域的领导者。网络的重点组织或国家应积极主动地发现、提出和建立与其他组织或国家的新关系,特别是与期刊网络边界的组织或国家的新关系,使整个网络更加整合和联系。知名成员帮助组织或国家招募新作者,并将他们连接到合作作者网络。本研究还使用概念链接分析来识别区块链文章的主要概念和语义结构。这可能会导致新作者在初级学科中发展研究思路或主题。
{"title":"An assessment of blockchain academia and news developments: a bibliometric and text-mining analysis","authors":"Chien-Wen Shen, Phung Phi Tran","doi":"10.1108/lht-10-2022-0473","DOIUrl":"https://doi.org/10.1108/lht-10-2022-0473","url":null,"abstract":"Purpose This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified. Design/methodology/approach To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures. Findings The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries. Research limitations/implications Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers. Originality/value This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136078432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-13DOI: 10.1108/lht-07-2023-0322
Mohd Afjal
Purpose The aim of the study is to understand the transformative impact of ChatGPT on artificial intelligence (AI) research, its applications, implications, challenges and potential to shape future AI trends. The study also seeks to assess the relevance and quality of research output through citation and bibliographic coupling analysis. Design/methodology/approach This study employed a comprehensive bibliometric analysis using Biblioshiny and VOSviewer to investigate the research trends, influential entities and leading contributors in the domain of AI, focusing on the ChatGPT model. Findings The analysis revealed a high prevalence of AI-related terms, indicating a significant interest in and engagement with ChatGPT in AI studies and applications. “Nature” and “Thorp H.H.” emerged as the most cited source and author, respectively, while the USA surfaced as the leading contributor in the field. Research limitations/implications While the findings provide a comprehensive overview of the ChatGPT research landscape, it is important to note that the conclusions drawn are only as current as the data used. Practical implications The study highlights potential collaboration opportunities and signals areas of research that might benefit from increased focus or diversification. It serves as a valuable resource for researchers, practitioners and policymakers for strategic planning and decision-making in AI research, specifically in relation to ChatGPT. Originality/value This study is one of the first to provide a comprehensive bibliometric analysis of the ChatGPT research domain, its multidimensional impact and potential. It offers valuable insights for a range of stakeholders in understanding the current landscape and future directions of ChatGPT in AI.
{"title":"ChatGPT and the AI revolution: a comprehensive investigation of its multidimensional impact and potential","authors":"Mohd Afjal","doi":"10.1108/lht-07-2023-0322","DOIUrl":"https://doi.org/10.1108/lht-07-2023-0322","url":null,"abstract":"Purpose The aim of the study is to understand the transformative impact of ChatGPT on artificial intelligence (AI) research, its applications, implications, challenges and potential to shape future AI trends. The study also seeks to assess the relevance and quality of research output through citation and bibliographic coupling analysis. Design/methodology/approach This study employed a comprehensive bibliometric analysis using Biblioshiny and VOSviewer to investigate the research trends, influential entities and leading contributors in the domain of AI, focusing on the ChatGPT model. Findings The analysis revealed a high prevalence of AI-related terms, indicating a significant interest in and engagement with ChatGPT in AI studies and applications. “Nature” and “Thorp H.H.” emerged as the most cited source and author, respectively, while the USA surfaced as the leading contributor in the field. Research limitations/implications While the findings provide a comprehensive overview of the ChatGPT research landscape, it is important to note that the conclusions drawn are only as current as the data used. Practical implications The study highlights potential collaboration opportunities and signals areas of research that might benefit from increased focus or diversification. It serves as a valuable resource for researchers, practitioners and policymakers for strategic planning and decision-making in AI research, specifically in relation to ChatGPT. Originality/value This study is one of the first to provide a comprehensive bibliometric analysis of the ChatGPT research domain, its multidimensional impact and potential. It offers valuable insights for a range of stakeholders in understanding the current landscape and future directions of ChatGPT in AI.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.1108/lht-04-2022-0168
Kaili Wang, Ke Dong, Jiachun Wu, Jiang Wu
Purpose The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking. Design/methodology/approach This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies. Findings Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion. Originality/value The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.
{"title":"Patterns of artificial intelligence policies in China: a nationwide perspective","authors":"Kaili Wang, Ke Dong, Jiachun Wu, Jiang Wu","doi":"10.1108/lht-04-2022-0168","DOIUrl":"https://doi.org/10.1108/lht-04-2022-0168","url":null,"abstract":"Purpose The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking. Design/methodology/approach This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies. Findings Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion. Originality/value The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135354037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-12DOI: 10.1108/lht-02-2023-0076
Sumei Yao, Fan Wang, Jing Chen, Quan Lu
Purpose Social media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods. Design/methodology/approach The authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles. Findings (1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife. Practical implications The authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression. Originality/value This article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.
近年来,社交媒体文本作为抑郁症研究的数据来源已成为信息管理与公共卫生之间的重要融合。本文旨在对社交媒体上的文本进行抑郁相关的研究进行梳理,特别注意研究主题和方法。作者最终选择了在Web of Science、Wiley、ACM Digital Library、EBSCO、IEEE Xplore和JMIR数据库中发表的研究文章,共57篇。(1)从编码结果来看,抑郁预测和语言特征与信息行为是两个最受欢迎的主题。病人需要的主题在过去几年中有了进展。然而,对病耻感和抗抑郁药的关注较少。(2)相对于定性方法,研究者更倾向于使用定量方法,如机器学习和统计分析。(4)从数据收集平台的分析来看,更多的研究者使用综合性社交媒体网站,如Reddit和Facebook,而不是针对抑郁症的社区,如Sunforum和Alonelylife。作者建议使用机器学习和统计分析来彻底探索与污名化和抗抑郁药相关的因素。此外,开展结合不同来源数据的混合方法研究将是有价值的。这些方法将为寻求全面了解抑郁症的决策者和制药公司提供有益的见解。这篇文章在系统地收集和研究社交媒体与抑郁症的健康相关文本的交叉点内的主题和方法方面做出了开创性的努力。
{"title":"Utilizing health-related text on social media for depression research: themes and methods","authors":"Sumei Yao, Fan Wang, Jing Chen, Quan Lu","doi":"10.1108/lht-02-2023-0076","DOIUrl":"https://doi.org/10.1108/lht-02-2023-0076","url":null,"abstract":"Purpose Social media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods. Design/methodology/approach The authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles. Findings (1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife. Practical implications The authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression. Originality/value This article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135824533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-12DOI: 10.1108/lht-04-2023-0138
Yunfei Xing, Yuming He, Justin Z. Zhang
Purpose The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic. Design/methodology/approach Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets. Findings Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map. Originality/value Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.
{"title":"Examining themes of social media users' opinion on remote work during COVID-19 pandemic: a justice theory perspective","authors":"Yunfei Xing, Yuming He, Justin Z. Zhang","doi":"10.1108/lht-04-2023-0138","DOIUrl":"https://doi.org/10.1108/lht-04-2023-0138","url":null,"abstract":"Purpose The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic. Design/methodology/approach Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets. Findings Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map. Originality/value Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":"285 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135824705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-11DOI: 10.1108/lht-02-2023-0031
Bwsrang Basumatary, M. Yuvaraj, Nitesh Kumar Verma, M. Verma
PurposeAdopting and implementing robotic technology applications in the library is a significant technological up-gradation today. The purpose of this study was to evaluate selected literature focused mainly on robotics technology applications in the field of libraries and to assess the online social attention to research publications.Design/methodology/approachThe study employed Scientometric and altmetric tools to evaluate the research publications. The bibliographic data of research publications were downloaded from Scopus database and scrutinized one by one and 71 articles were selected which mainly focused on robotic technology in libraries. Altmetric data were collected from the Dimensions.ai database. The analysis was performed using MS Excel, Tableau, Biblioshiny, VOSviewer and SPSS software.FindingsResearch on robotic technology in the field of libraries has been experiencing a gradual increase, marked by an annual growth rate of 12.93%. The United States has prominently led the way as the most active participant and collaborator in this advancement. Among the various journals, Library Hi Tech has notably stood out as a significant contributor to this field. However, the research articles have garnered limited social attention and impact. Furthermore, the patterns of authorship collaboration have demonstrated relatively modest levels within the field, and a weak correlation has been observed between the social attention received and the Scopus citation metrics of the publications.Practical implicationsThe research needs to be disseminated more through various social media platforms to increase its visibility. Sharing research information through social media can bridge the gap between academia and society. The findings of this study can serve as a valuable reference for researchers and policymakers.Originality/valueThis study presents a Scientometric analysis of the selected published literature on robotics technology applications in the field of libraries, highlighting the progress and development of worldwide research in this area.
{"title":"Mapping of the selected literature on robotic technology applications in libraries based on Scopus database: a subjective computational review","authors":"Bwsrang Basumatary, M. Yuvaraj, Nitesh Kumar Verma, M. Verma","doi":"10.1108/lht-02-2023-0031","DOIUrl":"https://doi.org/10.1108/lht-02-2023-0031","url":null,"abstract":"PurposeAdopting and implementing robotic technology applications in the library is a significant technological up-gradation today. The purpose of this study was to evaluate selected literature focused mainly on robotics technology applications in the field of libraries and to assess the online social attention to research publications.Design/methodology/approachThe study employed Scientometric and altmetric tools to evaluate the research publications. The bibliographic data of research publications were downloaded from Scopus database and scrutinized one by one and 71 articles were selected which mainly focused on robotic technology in libraries. Altmetric data were collected from the Dimensions.ai database. The analysis was performed using MS Excel, Tableau, Biblioshiny, VOSviewer and SPSS software.FindingsResearch on robotic technology in the field of libraries has been experiencing a gradual increase, marked by an annual growth rate of 12.93%. The United States has prominently led the way as the most active participant and collaborator in this advancement. Among the various journals, Library Hi Tech has notably stood out as a significant contributor to this field. However, the research articles have garnered limited social attention and impact. Furthermore, the patterns of authorship collaboration have demonstrated relatively modest levels within the field, and a weak correlation has been observed between the social attention received and the Scopus citation metrics of the publications.Practical implicationsThe research needs to be disseminated more through various social media platforms to increase its visibility. Sharing research information through social media can bridge the gap between academia and society. The findings of this study can serve as a valuable reference for researchers and policymakers.Originality/valueThis study presents a Scientometric analysis of the selected published literature on robotics technology applications in the field of libraries, highlighting the progress and development of worldwide research in this area.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48320816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.1108/lht-04-2023-0148
Weijie Zhu
PurposeThe research in this paper aims to investigate the development of Library and Information Science in Chinese universities. Specifically, it focuses on understanding the spatial and temporal aspects of subject knowledge output and providing a more comprehensive explanation of the imbalance in subject research.Design/methodology/approachThis study applies the bibliometric method to analyze 131,112 papers published by 51 universities in mainland China from 1977 to 2021, as recorded in the Chinese Social Sciences Citation Index (CSSCI). The study classifies the evolution trends of the discipline and quantifies the published article data of the universities using the index of published articles. Additionally, it examines the development status, structural situation, influencing factors and prospects of universities in different categories and regions.FindingsThe field of Library and Information Science is gaining momentum in Chinese universities, but there are significant differences in its development. While the relative gap among universities in a regional context is diminishing, the absolute gap in the category perspective is increasing. The development of Library and Information Science is influenced by various factors, including the academic environment, geographical position, scientific research projects and academic traditions. The uneven development of the discipline is maintained in the short term.Originality/valueThis paper proposes a new quantitative index of discipline development, the university publication index. This index allows for an examination of the temporal and spatial trends of discipline development using domestic universities as the subject of research. The paper presents an overview of discipline development through four aspects: academic participation practice, discipline governance mechanisms, education and teaching systems and discourse construction within the discipline. The theoretical support provided by this study can help facilitate innovative development in the discipline.
{"title":"How is the development of library and information science in China?","authors":"Weijie Zhu","doi":"10.1108/lht-04-2023-0148","DOIUrl":"https://doi.org/10.1108/lht-04-2023-0148","url":null,"abstract":"PurposeThe research in this paper aims to investigate the development of Library and Information Science in Chinese universities. Specifically, it focuses on understanding the spatial and temporal aspects of subject knowledge output and providing a more comprehensive explanation of the imbalance in subject research.Design/methodology/approachThis study applies the bibliometric method to analyze 131,112 papers published by 51 universities in mainland China from 1977 to 2021, as recorded in the Chinese Social Sciences Citation Index (CSSCI). The study classifies the evolution trends of the discipline and quantifies the published article data of the universities using the index of published articles. Additionally, it examines the development status, structural situation, influencing factors and prospects of universities in different categories and regions.FindingsThe field of Library and Information Science is gaining momentum in Chinese universities, but there are significant differences in its development. While the relative gap among universities in a regional context is diminishing, the absolute gap in the category perspective is increasing. The development of Library and Information Science is influenced by various factors, including the academic environment, geographical position, scientific research projects and academic traditions. The uneven development of the discipline is maintained in the short term.Originality/valueThis paper proposes a new quantitative index of discipline development, the university publication index. This index allows for an examination of the temporal and spatial trends of discipline development using domestic universities as the subject of research. The paper presents an overview of discipline development through four aspects: academic participation practice, discipline governance mechanisms, education and teaching systems and discourse construction within the discipline. The theoretical support provided by this study can help facilitate innovative development in the discipline.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43674894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.1108/lht-11-2022-0521
ZiYun Wang, Qingong Shi, Qunzhe Ding
PurposeThis investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.Design/methodology/approachIn this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.FindingsThe provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.Originality/valueIn this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.
{"title":"Evaluation and optimization of supply factor efficiency for public digital cultural services in China","authors":"ZiYun Wang, Qingong Shi, Qunzhe Ding","doi":"10.1108/lht-11-2022-0521","DOIUrl":"https://doi.org/10.1108/lht-11-2022-0521","url":null,"abstract":"PurposeThis investigation is designed to quantify and appraise the efficiency of resource distribution in the provision of public digital cultural services in China. By acknowledging and incorporating the realities of China's social development, the authors offer recommendations for enhancement derived from the study’s data analysis results. The research zeroes in on the dissection and analysis of the integral elements that structure the provision of public digital cultural services, and it concentrates on the associated data computation. The conclusions drawn herein are expected to serve as a significant point of reference for ongoing academic investigations and practical explorations in affiliated domains.Design/methodology/approachIn this research, the authors utilize a hybrid methodology to meticulously evaluate the efficiency of the components that underpin the provision of public digital cultural services (PDCS) in China. The authors embark on deconstructing the various constituents within the PDCS supply framework, conducting in-depth analyses and providing cogent interpretations of each integral element. Subsequently, the authors deploy the well-regarded SBM super-efficiency model to ascertain the operational efficiency of these components. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.FindingsThe provision of PDCS in China as of 2021 had been characterized by overall good efficiency, significant regional disparity and a disconnect between inputs and outputs with weak correlations to economic and demographic data.Originality/valueIn this study, the authors provide an exhaustive deconstruction and interpretation of the public digital cultural services supply system, thereby proposing a framework for evaluating the efficiency of supply element allocation. Additionally, the authors have determined a set of distinct measurable indicators that are readily accessible for open collection. Notably, this analytical and evaluative framework designed for element analysis and measurement may also find application in efficiency evaluation research of the supply systems of other related cultural endeavors.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49580874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial: Advances in information and knowledge management","authors":"Dickson K. W. Chiu, Kevin K. W. Ho","doi":"10.1108/lht-08-2023-588","DOIUrl":"https://doi.org/10.1108/lht-08-2023-588","url":null,"abstract":"","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44749096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}