Pub Date : 2023-06-13DOI: 10.1108/lht-04-2022-0193
Xiaoguang Wang, Yijun Gao, Z. Lu
PurposeMicroblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.Design/methodology/approachThe authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.FindingsMicroblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.Research limitations/implicationsFirst, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.Originality/valueThis study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.
{"title":"User influence and microblog marketing: a case study of Sina Weibo in China","authors":"Xiaoguang Wang, Yijun Gao, Z. Lu","doi":"10.1108/lht-04-2022-0193","DOIUrl":"https://doi.org/10.1108/lht-04-2022-0193","url":null,"abstract":"PurposeMicroblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.Design/methodology/approachThe authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.FindingsMicroblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.Research limitations/implicationsFirst, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.Originality/valueThis study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44682568","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 : 2023-06-13DOI: 10.1108/lht-12-2022-0560
A. Doulani, M. Hossaini
PurposeThis study aims to investigate the factors affecting the motivation of graduate students of information science in scientific and research activities and science production. This research is applied in terms of purpose and descriptive in terms of type and method.Design/methodology/approachThe study's statistical population includes all postgraduate information science students studying in public universities. The random sampling method was simple. The data collection tool was a questionnaire. Descriptive statistics and one-sample t-test, independent t-test, and ANOVA were used to analyze the collected data by SPSS software.FindingsFindings showed that all the main variables (internal motivations, external motivations, self-empowerment, and intellectual and specialized interactions) affect the participation of postgraduate students in research and scientific activities. Among the identified components, the creation of opportunities, research facilities, innovation, and formal relations between students and professors, has the most significant impact on students' motivation to participate in scientific and research activities and science production. There was no significant difference between education and age. From the results obtained from the present study, it can be said that the above variables, which were divided into four categories, with the intensity of the participation of graduate students of universities that in the present study examined the field of librarianship and information, with power and Or weakness are influential. This means that the students at the beginning of the research path, in other words, will be future researchers, should be constantly monitored as a source in the production of science.Originality/valueThis research is one of the few types of research that examines the influential variables in increasing the motivation to participate in the study, considering the population of postgraduate students of universities and scientific institutions as drivers of science production.
{"title":"What are the factors affecting the participation of postgraduate students in research processes? From motivational variables to demographic variables","authors":"A. Doulani, M. Hossaini","doi":"10.1108/lht-12-2022-0560","DOIUrl":"https://doi.org/10.1108/lht-12-2022-0560","url":null,"abstract":"PurposeThis study aims to investigate the factors affecting the motivation of graduate students of information science in scientific and research activities and science production. This research is applied in terms of purpose and descriptive in terms of type and method.Design/methodology/approachThe study's statistical population includes all postgraduate information science students studying in public universities. The random sampling method was simple. The data collection tool was a questionnaire. Descriptive statistics and one-sample t-test, independent t-test, and ANOVA were used to analyze the collected data by SPSS software.FindingsFindings showed that all the main variables (internal motivations, external motivations, self-empowerment, and intellectual and specialized interactions) affect the participation of postgraduate students in research and scientific activities. Among the identified components, the creation of opportunities, research facilities, innovation, and formal relations between students and professors, has the most significant impact on students' motivation to participate in scientific and research activities and science production. There was no significant difference between education and age. From the results obtained from the present study, it can be said that the above variables, which were divided into four categories, with the intensity of the participation of graduate students of universities that in the present study examined the field of librarianship and information, with power and Or weakness are influential. This means that the students at the beginning of the research path, in other words, will be future researchers, should be constantly monitored as a source in the production of science.Originality/valueThis research is one of the few types of research that examines the influential variables in increasing the motivation to participate in the study, considering the population of postgraduate students of universities and scientific institutions as drivers of science production.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48373523","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 : 2023-05-30DOI: 10.1108/lht-01-2022-0078
Asad Javed, S. Khan, M. A. S. Khan, H. Shah
PurposeThe study was initiated to test the relationship of social media site addiction on librarians' performance. Furthermore, the study also tested the mediating role of task distraction and moderating role of effective self-control in aforesaid relationship.Design/methodology/approachThis was an empirical study, and data for the research were collected through a standardized questionnaire from 503 librarians who were having Facebook accounts and are questionnaire developed through “Google Forms” and the link of the questionnaire was distributed using Facebook groups. Data was analyzed using descriptive analysis, correlation, Baron and Kenny's approach, and Normal Test Theory.FindingsResults indicate that social media addiction is an important factor for that is reducing librarians' performance. At the same time task distraction also adds to negative impact of social media addiction on librarians' performance. However, effective self-control can reduce the negative impact of social media addiction on their performance.Research limitations/implicationsThis research has some important theoretical as well as practical implications for librarians, library management, and well as for policy makers and government.Originality/valueSocial media is commonly used for communication but when it becomes addiction, it can reduce the employees' performance. Most of existing researched focused on positive aspects of social media; only few researches explored the negative impacts of social media. The proposed relationship was never tested on librarians. This study filled this literature gap and proposed as well as empirically tested a model for evaluating negative impact of social media on librarians' performance.
{"title":"Impact of social media addiction on librarians' performance: mediating role of task distraction, moderating role of effective self-control","authors":"Asad Javed, S. Khan, M. A. S. Khan, H. Shah","doi":"10.1108/lht-01-2022-0078","DOIUrl":"https://doi.org/10.1108/lht-01-2022-0078","url":null,"abstract":"PurposeThe study was initiated to test the relationship of social media site addiction on librarians' performance. Furthermore, the study also tested the mediating role of task distraction and moderating role of effective self-control in aforesaid relationship.Design/methodology/approachThis was an empirical study, and data for the research were collected through a standardized questionnaire from 503 librarians who were having Facebook accounts and are questionnaire developed through “Google Forms” and the link of the questionnaire was distributed using Facebook groups. Data was analyzed using descriptive analysis, correlation, Baron and Kenny's approach, and Normal Test Theory.FindingsResults indicate that social media addiction is an important factor for that is reducing librarians' performance. At the same time task distraction also adds to negative impact of social media addiction on librarians' performance. However, effective self-control can reduce the negative impact of social media addiction on their performance.Research limitations/implicationsThis research has some important theoretical as well as practical implications for librarians, library management, and well as for policy makers and government.Originality/valueSocial media is commonly used for communication but when it becomes addiction, it can reduce the employees' performance. Most of existing researched focused on positive aspects of social media; only few researches explored the negative impacts of social media. The proposed relationship was never tested on librarians. This study filled this literature gap and proposed as well as empirically tested a model for evaluating negative impact of social media on librarians' performance.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42172948","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 : 2023-05-29DOI: 10.1108/lht-11-2022-0538
Xiang Zheng, Mingjie Li, Ze Wan, Yan Zhang
PurposeThis study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.Design/methodology/approachThis study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.FindingsThe knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.Originality/valueThis study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.
{"title":"Knowledge mining and graph visualization of ancient Chinese scientific and technological documents bibliographic summaries based on digital humanities","authors":"Xiang Zheng, Mingjie Li, Ze Wan, Yan Zhang","doi":"10.1108/lht-11-2022-0538","DOIUrl":"https://doi.org/10.1108/lht-11-2022-0538","url":null,"abstract":"PurposeThis study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.Design/methodology/approachThis study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.FindingsThe knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.Originality/valueThis study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44048970","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 : 2023-05-24DOI: 10.1108/lht-06-2021-0194
H. Hussain, J. Wen, Renai Jiang, Junaid Waheed, Waheed Ali, N. Khan
PurposeIn light of the shift in focus from information communication technology (ICT) access (access divide) and skills (skills divide) to the tangible impacts of ICT use (impact divide), a growing number of scholars have called for further investigation into the inter-territorial and multi-dimensional aspects of the digital divide in China. This study aims to address these gaps by examining the disparities across 31 provinces, particularly emphasizing the transition from the traditional access and skills divides to the impact divide.Design/methodology/approachMultivariate regression analysis extensively investigates the transition from the access and skills divides to the impact divide across 31 provinces. Additionally, ArcGIS software is used to analyze spatial agglomeration and the auto-correlation (Moran-i) and predict mapping patterns in the data corresponding to all three levels of the digital divide.FindingsAccording to the study's findings, poverty is a significant factor in the digital divide between different regions in China. The research shows that provinces with advanced administrative systems, such as Guangdong, Shanghai, Beijing, Jiangsu, Shandon and Zhejiang, have high scores on the digital development index (DDI). However, regions with poverty-ridden and rural areas, primarily located in southwest, central and western China, tend to have lower DDI scores.Originality/valueThis study offers a novel contribution to the literature by presenting an innovative conceptual framework that explores the impact divide within China's provinces. The authors also address this lacuna in the literature by developing and testing two dimensions to examine the relationships statistically under a wide range of socioeconomic and ICT indicators.
{"title":"Analyzing the role of ICT in bridging the digital divide: a transitional analytical framework for ICT access to impact","authors":"H. Hussain, J. Wen, Renai Jiang, Junaid Waheed, Waheed Ali, N. Khan","doi":"10.1108/lht-06-2021-0194","DOIUrl":"https://doi.org/10.1108/lht-06-2021-0194","url":null,"abstract":"PurposeIn light of the shift in focus from information communication technology (ICT) access (access divide) and skills (skills divide) to the tangible impacts of ICT use (impact divide), a growing number of scholars have called for further investigation into the inter-territorial and multi-dimensional aspects of the digital divide in China. This study aims to address these gaps by examining the disparities across 31 provinces, particularly emphasizing the transition from the traditional access and skills divides to the impact divide.Design/methodology/approachMultivariate regression analysis extensively investigates the transition from the access and skills divides to the impact divide across 31 provinces. Additionally, ArcGIS software is used to analyze spatial agglomeration and the auto-correlation (Moran-i) and predict mapping patterns in the data corresponding to all three levels of the digital divide.FindingsAccording to the study's findings, poverty is a significant factor in the digital divide between different regions in China. The research shows that provinces with advanced administrative systems, such as Guangdong, Shanghai, Beijing, Jiangsu, Shandon and Zhejiang, have high scores on the digital development index (DDI). However, regions with poverty-ridden and rural areas, primarily located in southwest, central and western China, tend to have lower DDI scores.Originality/valueThis study offers a novel contribution to the literature by presenting an innovative conceptual framework that explores the impact divide within China's provinces. The authors also address this lacuna in the literature by developing and testing two dimensions to examine the relationships statistically under a wide range of socioeconomic and ICT indicators.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44070891","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 : 2023-05-11DOI: 10.1108/lht-10-2022-0477
Shivangi Verma, N. Garg
PurposeWith the growth and profound influence of technology on our life, it is important to address the ethical issues inherent to the development and deployment of technology. Researchers and practitioners submit the need to inspect: how technology and ethics interact, how ethical principles regulate technology and what could be the probable future course of action to execute techno-ethical practices in a socio-technical discourse effectively. To address the thoughts related to techno-ethics, the authors of the present study conducted exploratory research to understand the trend and relevance of technology ethics since its inception.Design/methodology/approachThe study collected over 679 documents for the period 1990–2022 from the Scopus database. A quantitative approach of bibliometric analysis was conducted to study the pattern of authorship, publications, citations, prominent journals and contributors in the subject area. VOS viewer software was utilized to visualize and map academic performance in techno-ethics.FindingsThe findings revealed that the concept of techno-ethics is an emerging field and requires more investigation to harness its relevance with everchanging technology development. The data revealed substantial growth in the field of techno-ethics in humanities, social science and management domain in the last two decades. Also, most of the prominent cited references and documents in the database tend to cover the theme of Artificial Intelligence, Big data, computer ethics, morality, decision-making, IT ethics, human rights, responsibility and privacy.Originality/valueThe article provides a comprehensive overview of scientific production and main research trends in techno-ethics until 2022. The study is a pioneer in expanding the academic productivity and performance of embedding ethics in technology.
{"title":"The trend and future of techno-ethics: a bibliometric analysis of three decades","authors":"Shivangi Verma, N. Garg","doi":"10.1108/lht-10-2022-0477","DOIUrl":"https://doi.org/10.1108/lht-10-2022-0477","url":null,"abstract":"PurposeWith the growth and profound influence of technology on our life, it is important to address the ethical issues inherent to the development and deployment of technology. Researchers and practitioners submit the need to inspect: how technology and ethics interact, how ethical principles regulate technology and what could be the probable future course of action to execute techno-ethical practices in a socio-technical discourse effectively. To address the thoughts related to techno-ethics, the authors of the present study conducted exploratory research to understand the trend and relevance of technology ethics since its inception.Design/methodology/approachThe study collected over 679 documents for the period 1990–2022 from the Scopus database. A quantitative approach of bibliometric analysis was conducted to study the pattern of authorship, publications, citations, prominent journals and contributors in the subject area. VOS viewer software was utilized to visualize and map academic performance in techno-ethics.FindingsThe findings revealed that the concept of techno-ethics is an emerging field and requires more investigation to harness its relevance with everchanging technology development. The data revealed substantial growth in the field of techno-ethics in humanities, social science and management domain in the last two decades. Also, most of the prominent cited references and documents in the database tend to cover the theme of Artificial Intelligence, Big data, computer ethics, morality, decision-making, IT ethics, human rights, responsibility and privacy.Originality/valueThe article provides a comprehensive overview of scientific production and main research trends in techno-ethics until 2022. The study is a pioneer in expanding the academic productivity and performance of embedding ethics in technology.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43358524","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 : 2023-05-09DOI: 10.1108/lht-08-2022-0361
Dan Wang
PurposeThis research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.Design/methodology/approachA total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.FindingsThe People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.Research limitations/implicationsThis study helps librarians, scientists and funders understand smart library trends.Originality/valueThere are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.
目的本研究对全球智能图书馆进行文献计量分析和网络映射。它审查出版物概况，确定被引用最多的出版物和首选来源，并考虑全球作者，组织和国家的合作。该研究还强调了关键词趋势和集群，并从共被引参考文献网络中发现了新的发展和新兴趋势。设计/方法/方法从Web of Science数据库中提取2003年至2021年共264条记录，1200次引用。利用BibExcel、VOSviewer、Biblioshiny和CiteSpace对智能图书馆的发展趋势进行了分析和可视化。结果:中国发表论文最多(119篇)，被引用次数最多(374篇)，h指数最高(12篇)，总链接强度最高(TLS = 25)。其中武汉大学的h指数最高(6)，香港大学的Chiu, Dickson k.w. (H-index = 4, TLS = 22)和Lo, Patrick (H-index = 4, TLS = 21)的h指数最高，也是最合作的作者。图书馆高科技是最受欢迎的期刊。“移动图书馆”是使用频率最高的关键词。“移动环境”是研究前沿最大的集群。本研究有助于图书馆员、科学家和资助者了解智能图书馆的发展趋势。独创性/价值关于智能图书馆的研究有很多，背景研究也很扎实。然而，据作者所知，这项研究是第一次对全球智能图书馆进行文献计量分析和网络测绘。
{"title":"Bibliometric analyses and network mapping on the smart library in Web of Science from 2003 to 2021","authors":"Dan Wang","doi":"10.1108/lht-08-2022-0361","DOIUrl":"https://doi.org/10.1108/lht-08-2022-0361","url":null,"abstract":"PurposeThis research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.Design/methodology/approachA total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.FindingsThe People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.Research limitations/implicationsThis study helps librarians, scientists and funders understand smart library trends.Originality/valueThere are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42672635","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 : 2023-05-09DOI: 10.1108/lht-03-2022-0150
M. Mirzabeigi, Mahsa Torabi, Tahere Jowkar
PurposeThe objective of this study was to investigate the impacts of personality traits and the ability to detect fake news on information avoidance behavior. It also examined the effect of personality traits on the ability to detect fake news.Design/methodology/approachThe sample population included Shiraz University students who were studying in the second semester of academic year 2021 in different academic levels. It consisted of 242 students of Shiraz University. The Big Five theory was used as the theoretical background of the study. Moreover, the research instrument was an electronic questionnaire consisting of the three questionnaires of the ability to detect fake news (Esmaeili et al., 2019, inspired by IFLA, 2017), the Big Five personality traits (Goldberg, 1999) and information avoidance (Howell and Shepperd, 2016). The statistical methods used to analyze the data were Pearson correlation and stepwise regression, which were performed through SPSS software (version 26).FindingsThe results showed that from among the five main personality factors, only neuroticism had a positive and significant effect on information avoidance. In addition, the ability to detect fake news had a significant negative effect on information avoidance behavior. Further analyses also showed positive and significant effects of openness to experience and extraversion on the ability to detect fake news. In fact, the former had more predictive power.Practical implicationsFollowing the Big Five theory considering COVID-19 information avoidance and the ability to detect COVID-19 fake news, this study shifted the focus from environmental factors to personality factors and personality traits. Furthermore, this study introduced the ability to detect fake news as an influential factor in health information avoidance behaviors, which can be a prelude for new research studies.Originality/valueThe present study applied the five main personality factors theory in the context of information avoidance behavior and the ability to detect fake news, and supported the effect of personality traits on these variables.
目的本研究旨在探讨人格特征和发现假新闻的能力对信息回避行为的影响。研究还考察了人格特征对发现假新闻能力的影响。设计/方法论/方法样本人群包括设拉子大学2021学年下学期不同学术水平的学生。它由设拉子大学的242名学生组成。本研究以“五大”理论为理论背景。此外，该研究工具是一份电子问卷，由三个问卷组成，即检测假新闻的能力（Esmaeili et al.，2019，受IFLA启发，2017）、五大人格特征（Goldberg，1999）和信息回避（Howell和Shepperd，2016）。结果表明，在5个主要人格因素中，只有神经质对信息回避有正向显著影响。此外，发现假新闻的能力对信息回避行为有显著的负面影响。进一步的分析还显示，经验开放性和外向性对检测假新闻的能力产生了积极而显著的影响。事实上，前者更有预测力。实践含义根据考虑新冠肺炎信息规避和新冠肺炎假新闻检测能力的五大理论，本研究将重点从环境因素转移到人格因素和人格特征。此外，本研究引入了检测假新闻的能力作为健康信息回避行为的影响因素，这可能是新研究的前奏。原创性/价值本研究将五大人格因素理论应用于信息回避行为和发现假新闻的能力，并支持人格特征对这些变量的影响。
{"title":"The role of personality traits and the ability to detect fake news in predicting information avoidance during the COVID-19 pandemic","authors":"M. Mirzabeigi, Mahsa Torabi, Tahere Jowkar","doi":"10.1108/lht-03-2022-0150","DOIUrl":"https://doi.org/10.1108/lht-03-2022-0150","url":null,"abstract":"PurposeThe objective of this study was to investigate the impacts of personality traits and the ability to detect fake news on information avoidance behavior. It also examined the effect of personality traits on the ability to detect fake news.Design/methodology/approachThe sample population included Shiraz University students who were studying in the second semester of academic year 2021 in different academic levels. It consisted of 242 students of Shiraz University. The Big Five theory was used as the theoretical background of the study. Moreover, the research instrument was an electronic questionnaire consisting of the three questionnaires of the ability to detect fake news (Esmaeili et al., 2019, inspired by IFLA, 2017), the Big Five personality traits (Goldberg, 1999) and information avoidance (Howell and Shepperd, 2016). The statistical methods used to analyze the data were Pearson correlation and stepwise regression, which were performed through SPSS software (version 26).FindingsThe results showed that from among the five main personality factors, only neuroticism had a positive and significant effect on information avoidance. In addition, the ability to detect fake news had a significant negative effect on information avoidance behavior. Further analyses also showed positive and significant effects of openness to experience and extraversion on the ability to detect fake news. In fact, the former had more predictive power.Practical implicationsFollowing the Big Five theory considering COVID-19 information avoidance and the ability to detect COVID-19 fake news, this study shifted the focus from environmental factors to personality factors and personality traits. Furthermore, this study introduced the ability to detect fake news as an influential factor in health information avoidance behaviors, which can be a prelude for new research studies.Originality/valueThe present study applied the five main personality factors theory in the context of information avoidance behavior and the ability to detect fake news, and supported the effect of personality traits on these variables.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42230457","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 : 2023-05-01DOI: 10.1108/lht-12-2022-0556
Guijie Zhang, Fangfang Wei, Peixin Wang
PurposeThis paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.Design/methodology/approachPublications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.FindingsThe annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.Originality/valueThis paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.
{"title":"Opening the black box of Library Hi Tech: a social network and bibliometric analysis","authors":"Guijie Zhang, Fangfang Wei, Peixin Wang","doi":"10.1108/lht-12-2022-0556","DOIUrl":"https://doi.org/10.1108/lht-12-2022-0556","url":null,"abstract":"PurposeThis paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.Design/methodology/approachPublications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.FindingsThe annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.Originality/valueThis paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46416816","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 : 2023-04-28DOI: 10.1108/lht-08-2022-0400
Xiaohua Shi, Chen Hao, Ding Yue, Hongtao Lu
PurposeTraditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.Design/methodology/approachThe authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.FindingsThe authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.Research limitations/implicationsIt requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.Practical implicationsThe embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.Originality/valueThe proposed method is a practical embedding-driven model that accurately captures diverse user preferences.
{"title":"Library book recommendation with CNN-FM deep learning approach","authors":"Xiaohua Shi, Chen Hao, Ding Yue, Hongtao Lu","doi":"10.1108/lht-08-2022-0400","DOIUrl":"https://doi.org/10.1108/lht-08-2022-0400","url":null,"abstract":"PurposeTraditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.Design/methodology/approachThe authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.FindingsThe authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.Research limitations/implicationsIt requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.Practical implicationsThe embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.Originality/valueThe proposed method is a practical embedding-driven model that accurately captures diverse user preferences.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41735479","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}
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：