Pub Date : 2023-03-07DOI: 10.1108/gkmc-07-2022-0159
Nazia Wahid, U. Amin, Muhammad Ajmal Khan, Nadeem Siddique, N. Warraich
Purpose This study aims to map the “Desktop Research” (DR) output in Pakistan, as part of the growing field of research globally. It also ascertains the productive institutions and prolific authors along with their collaboration patterns. Design/methodology/approach Bibliometric techniques were used to quantitatively analyze the DR published in Pakistan. The publications from 1981 to 2021 were retrieved from Scopus. A total of 1,802 publications were retrieved and used for analysis. Findings Results indicated an unpredictable increase in DR output from approximately 100 to 400 records during the past five years. The year 2020 was most productive in DR research showing the excess use of secondary data by researchers in COVID-19. The focus of researchers towards DR was consistently rising. Medical journals were found to publish DR extensively. Majority of the publications were contributed by collaborative work and researchers of the USA were found as the most collaborative with Pakistani authors. Publications of single category journals, open access journals and international collaboration get more citations. Research limitations/implications The results of the analysis rely only on a single database, Scopus, for retrieving the publication data. Practical implications The study has practical implications for the policymakers and higher education development organizations to introduce the DR as a course in academic schools. Originality/value To the best of the authors’ knowledge, this study is the first to review DR in the context of Pakistan through bibliometric analysis. This comprehensive overview provides a better understanding of the development of the field and possible practice implications.
{"title":"Mapping the desktop research in Pakistan: a bibliometric analysis","authors":"Nazia Wahid, U. Amin, Muhammad Ajmal Khan, Nadeem Siddique, N. Warraich","doi":"10.1108/gkmc-07-2022-0159","DOIUrl":"https://doi.org/10.1108/gkmc-07-2022-0159","url":null,"abstract":"\u0000Purpose\u0000This study aims to map the “Desktop Research” (DR) output in Pakistan, as part of the growing field of research globally. It also ascertains the productive institutions and prolific authors along with their collaboration patterns.\u0000\u0000\u0000Design/methodology/approach\u0000Bibliometric techniques were used to quantitatively analyze the DR published in Pakistan. The publications from 1981 to 2021 were retrieved from Scopus. A total of 1,802 publications were retrieved and used for analysis.\u0000\u0000\u0000Findings\u0000Results indicated an unpredictable increase in DR output from approximately 100 to 400 records during the past five years. The year 2020 was most productive in DR research showing the excess use of secondary data by researchers in COVID-19. The focus of researchers towards DR was consistently rising. Medical journals were found to publish DR extensively. Majority of the publications were contributed by collaborative work and researchers of the USA were found as the most collaborative with Pakistani authors. Publications of single category journals, open access journals and international collaboration get more citations.\u0000\u0000\u0000Research limitations/implications\u0000The results of the analysis rely only on a single database, Scopus, for retrieving the publication data.\u0000\u0000\u0000Practical implications\u0000The study has practical implications for the policymakers and higher education development organizations to introduce the DR as a course in academic schools.\u0000\u0000\u0000Originality/value\u0000To the best of the authors’ knowledge, this study is the first to review DR in the context of Pakistan through bibliometric analysis. This comprehensive overview provides a better understanding of the development of the field and possible practice implications.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86199213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1108/gkmc-08-2022-0192
Sheikh Shueb, Sumeer Gul
Purpose The purpose of this study is to determine the funding ratio of BRICS nations in various research areas. The leading funding institutions that support research in the developing world have also been researched. Design/methodology/approach This study involves the funding acknowledgment analysis of the data retrieved from the “Clarivate Analytics' InCites database” under “22 specific research areas” to determine whether the publication was funded. Findings This study shows that China achieves the highest funding ratio of 88.6%, followed by Brazil (73.74%), Russia (72.93%) and South Africa (70.94%). However, India has the lowest funding ratio of 58.2%. For the subject areas, the highest funding ratio is by microbiology in Russia (86.6%), India (84.3%) and China (96.9%) and space science in Brazil (93.7%) and South Africa (94.82%). However, economics and business achieves the lowest funding ratio in Brazil (38.6%), India (20.1%) and South Africa (30.24%). Moreover, the regional funding agencies are the leading research sponsors in the BRICS nations. Practical implications This study implies increasing the funding ratio across various research areas, including arts, humanities and social sciences. The nations, particularly India, also need to gear up sponsoring the research to improve the funding ratio for scientific development, bringing overall good. Originality/value This study efforts to show the status of countries and research subjects in terms of funding ratio and reveals the prominent funders working toward scientific growth.
{"title":"Measuring the research funding landscape: a case study of BRICS nations","authors":"Sheikh Shueb, Sumeer Gul","doi":"10.1108/gkmc-08-2022-0192","DOIUrl":"https://doi.org/10.1108/gkmc-08-2022-0192","url":null,"abstract":"\u0000Purpose\u0000The purpose of this study is to determine the funding ratio of BRICS nations in various research areas. The leading funding institutions that support research in the developing world have also been researched.\u0000\u0000\u0000Design/methodology/approach\u0000This study involves the funding acknowledgment analysis of the data retrieved from the “Clarivate Analytics' InCites database” under “22 specific research areas” to determine whether the publication was funded.\u0000\u0000\u0000Findings\u0000This study shows that China achieves the highest funding ratio of 88.6%, followed by Brazil (73.74%), Russia (72.93%) and South Africa (70.94%). However, India has the lowest funding ratio of 58.2%. For the subject areas, the highest funding ratio is by microbiology in Russia (86.6%), India (84.3%) and China (96.9%) and space science in Brazil (93.7%) and South Africa (94.82%). However, economics and business achieves the lowest funding ratio in Brazil (38.6%), India (20.1%) and South Africa (30.24%). Moreover, the regional funding agencies are the leading research sponsors in the BRICS nations.\u0000\u0000\u0000Practical implications\u0000This study implies increasing the funding ratio across various research areas, including arts, humanities and social sciences. The nations, particularly India, also need to gear up sponsoring the research to improve the funding ratio for scientific development, bringing overall good.\u0000\u0000\u0000Originality/value\u0000This study efforts to show the status of countries and research subjects in terms of funding ratio and reveals the prominent funders working toward scientific growth.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87467755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-06-2022-0131
Faten Hamad, Maha Al-Fadel, A. Shehata
Purpose Technological advancement has forced academic libraries to change their traditional services and routines by adopting emerging technologies to respond to the changing information needs of their users who are now more technologically inclined and prefer to access information remotely and in a timely manner. Smart technologies are the recent trends in academic libraries. This research aims to investigate the level of smart information service implementation at academic libraries in Jordan. It also aimed to investigate the correlation between the level of smart information services offered by the libraries and the level of digital competencies among the library staff. Design/methodology/approach This research is designed using survey design to collect comprehensive information from the study participants. A questionnaire was disseminated to 340 respondents, and 246 questionnaires were returned and were suitable for analysis with a response rate of 72.4%. Findings The results indicated a moderate level of smart information service offered by academic libraries, as well as a moderate level of digital skills associated with the advocacy of smart information services. The results also indicated a strong and positive relationship between the level of smart information services at the investigated libraries and the level of digital competencies among the librarians. Practical implications The findings will help other academic libraries understand how to respond to the emergent change in users’ information-seeking behavior by understanding their available human resources competencies and the requirement to undergo this emergent change. Originality/value This paper provides insights and practical solutions for academic libraries in response to global information trends based on users’ behaviors. This research was conducted in Jordan as one of the developing countries and hence it provides insights of the situation there. It will help academic libraries in Jordan and the region to handle and cope with the challenges associated with technology acceptance based on its staff level of digital competencies. The contribution of this research that it was done in a developing country where progress in the filed can be considered slow because of many factors, mainly economics, where institutions focus on essential library objectives, which are information resources development and databases subscriptions.
{"title":"The level of digital competencies for the provision of smart information service at academic libraries in Jordan","authors":"Faten Hamad, Maha Al-Fadel, A. Shehata","doi":"10.1108/gkmc-06-2022-0131","DOIUrl":"https://doi.org/10.1108/gkmc-06-2022-0131","url":null,"abstract":"\u0000Purpose\u0000Technological advancement has forced academic libraries to change their traditional services and routines by adopting emerging technologies to respond to the changing information needs of their users who are now more technologically inclined and prefer to access information remotely and in a timely manner. Smart technologies are the recent trends in academic libraries. This research aims to investigate the level of smart information service implementation at academic libraries in Jordan. It also aimed to investigate the correlation between the level of smart information services offered by the libraries and the level of digital competencies among the library staff.\u0000\u0000\u0000Design/methodology/approach\u0000This research is designed using survey design to collect comprehensive information from the study participants. A questionnaire was disseminated to 340 respondents, and 246 questionnaires were returned and were suitable for analysis with a response rate of 72.4%.\u0000\u0000\u0000Findings\u0000The results indicated a moderate level of smart information service offered by academic libraries, as well as a moderate level of digital skills associated with the advocacy of smart information services. The results also indicated a strong and positive relationship between the level of smart information services at the investigated libraries and the level of digital competencies among the librarians.\u0000\u0000\u0000Practical implications\u0000The findings will help other academic libraries understand how to respond to the emergent change in users’ information-seeking behavior by understanding their available human resources competencies and the requirement to undergo this emergent change.\u0000\u0000\u0000Originality/value\u0000This paper provides insights and practical solutions for academic libraries in response to global information trends based on users’ behaviors. This research was conducted in Jordan as one of the developing countries and hence it provides insights of the situation there. It will help academic libraries in Jordan and the region to handle and cope with the challenges associated with technology acceptance based on its staff level of digital competencies. The contribution of this research that it was done in a developing country where progress in the filed can be considered slow because of many factors, mainly economics, where institutions focus on essential library objectives, which are information resources development and databases subscriptions.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73477828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-02-2022-0034
Zeinab Zaremohzzabieh, Roziah Mohd Rasdi
Purpose The existing literature on knowledge-sharing (KS) behavior in the organizational context demonstrates that there is diversity, if not divergence, in understanding KS. Thus, this paper aims to integrate social cognitive theory and social exchange theory to construct a research model for determining the incentive for knowledge sharing among individuals in organizations based on past empirical results. Design/methodology/approach Accordingly, the methodology adopted in this study is the meta-analytic structural equation modeling based on the data gathered from 78 studies (80 samples, n = 29,318). Findings The most significant predictors of KSB were organizational support and social interaction ties, whereby KS intention and attitude were most optimally predicted by organizational commitment, knowledge self-efficacy, social interaction ties, organizational expectancy and reciprocal benefit. This study carried out a moderation analysis to look into potential causes of inconsistent results. Originality/value This meta-analysis shows the most influencing factors that trigger KSB in organizations. Moreover, this study clarifies the possible reasons for the inconsistent findings of the previous studies. Thus, it contributes to the KS literature.
{"title":"Revisiting the determinants of knowledge-sharing behavior in organizations: a meta-analytic structural equation model application","authors":"Zeinab Zaremohzzabieh, Roziah Mohd Rasdi","doi":"10.1108/gkmc-02-2022-0034","DOIUrl":"https://doi.org/10.1108/gkmc-02-2022-0034","url":null,"abstract":"\u0000Purpose\u0000The existing literature on knowledge-sharing (KS) behavior in the organizational context demonstrates that there is diversity, if not divergence, in understanding KS. Thus, this paper aims to integrate social cognitive theory and social exchange theory to construct a research model for determining the incentive for knowledge sharing among individuals in organizations based on past empirical results.\u0000\u0000\u0000Design/methodology/approach\u0000Accordingly, the methodology adopted in this study is the meta-analytic structural equation modeling based on the data gathered from 78 studies (80 samples, n = 29,318).\u0000\u0000\u0000Findings\u0000The most significant predictors of KSB were organizational support and social interaction ties, whereby KS intention and attitude were most optimally predicted by organizational commitment, knowledge self-efficacy, social interaction ties, organizational expectancy and reciprocal benefit. This study carried out a moderation analysis to look into potential causes of inconsistent results.\u0000\u0000\u0000Originality/value\u0000This meta-analysis shows the most influencing factors that trigger KSB in organizations. Moreover, this study clarifies the possible reasons for the inconsistent findings of the previous studies. Thus, it contributes to the KS literature.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88719237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-08-2022-0207
N. Barik
Purpose This study aims to examine the research output on digital divide from 2001 to 2020 and measure the qualitative and quantitative growth of literature during the stated period by using required bibliometric measures for identifying the types of documents, yearly growth, country productivity, citation network of collaborative countries, authorship pattern, top authors, cocitation networks and assorted facets. Design/methodology/approach Web of Science database was used to retrieve the required data for this study. Keeping the objectives of this study in mind, the keyword “Digital Divide” was used as the search term. Moreover, the retrieved data were limited from the year 2001 to 2020 for two decades. A total of 5,518 publications were filtered and focused for subsequent facet-wise analysis and interpretation. Required bibliometric indicators like types of documents, yearly growth, authorship pattern, degree of collaboration (DC), country productivity, h-index and citation impact were used to study various dimensions of publication trends. VOSviewer software was used to visualize the authorship network, bibliographic coupling and keyword occurrences. Findings This study finds a total of 5,518 publications on the topic digital divide contributed by 14,277 authors from 130 countries across the world published through 2,843 source titles in 13 global languages during the past two decades (2001–2020). The annual growth of publications (AGP) on the topic digital divide shows 38.43% AGP globally. Journal articles have been identified as the preferred type of document with 73.11% of the literature. The DC indicates a healthy trend of collaborative research with a mean value of 0.70. The USA is the table topper with the contribution of 1,933(35.03%) publications and 77 h-index and James J., from Tilburg University, The Netherlands, is identified as top amongst the most productive authors with the highest number of 34 publications (h-index 14). Research limitations/implications This study restricts its scope on research productivity to the theme “digital divide” regarding authorship pattern, DC, most productive authors, most productive countries, most published sources and other key facets. This study exclusively refers to the Web of Science database in retrieving the required data. Moreover, this study takes global research into account with no geographical or language limitations and comprehends literature on digital divide for two decades ranging from the years 2001 to 2020. Practical implications Teachers and research scholars interested in bibliometric studies can benefit from insights into the scholarly documents published on the topic digital divide from 2001 to 2020. Originality/value This study yields some interesting findings on published literature on the digital divide during the past two decades relating to the most striking contributions, highly cited journals, the most prolific authors, country productivity, keyword cooccurre
目的研究2001 - 2020年数字鸿沟研究成果，采用文献计量学方法对文献类型、年增长率、国家生产率、合作国家引文网络、作者模式、顶级作者、引文网络等方面进行定性和定量分析。设计/方法/方法使用web of Science数据库检索本研究所需的数据。考虑到本研究的目的，关键词“数字鸿沟”被用作搜索词。此外，检索到的数据仅限于2001年至2020年的二十年。共有5 518份出版物经过筛选和集中，以便随后进行面向方面的分析和解释。使用文献类型、年增长率、作者模式、合作程度(DC)、国家生产力、h指数和引文影响等必要的文献计量指标来研究出版趋势的各个维度。使用VOSviewer软件对作者网络、书目耦合和关键词出现情况进行可视化。本研究发现，在过去二十年(2001-2020年)中，来自全球130个国家的14277位作者共发表了5518篇关于数字鸿沟的出版物，以13种全球语言通过2843种源标题出版。在全球范围内，关于数字鸿沟主题的出版物的年增长率为38.43%。期刊文章被确定为首选的文献类型，占文献的73.11%。合作研究发展趋势良好，平均值为0.70。美国以1933篇(35.03%)论文和77篇h指数排名第一，来自荷兰蒂尔堡大学的James J.被认为是最具生产力的作者之一，发表了34篇论文(h指数14)。本研究将其研究生产力的范围限制在作者模式、DC、最高产作者、最高产国家、最高产来源和其他关键方面的“数字鸿沟”主题上。本研究仅参考Web of Science数据库检索所需数据。此外，本研究考虑了全球研究，没有地域或语言限制，并理解了2001年至2020年二十年来关于数字鸿沟的文献。对文献计量学研究感兴趣的教师和研究学者可以从2001年至2020年发表的关于数字鸿沟主题的学术文献的见解中受益。原创性/价值本研究对过去二十年中有关数字鸿沟的已发表文献进行了一些有趣的发现，涉及最显著的贡献、高被引期刊、最多产的作者、国家生产率、关键词协同率和各种参数。
{"title":"Global research on digital divide during the past two decades: a bibliometric study of Web of Science indexed literature","authors":"N. Barik","doi":"10.1108/gkmc-08-2022-0207","DOIUrl":"https://doi.org/10.1108/gkmc-08-2022-0207","url":null,"abstract":"\u0000Purpose\u0000This study aims to examine the research output on digital divide from 2001 to 2020 and measure the qualitative and quantitative growth of literature during the stated period by using required bibliometric measures for identifying the types of documents, yearly growth, country productivity, citation network of collaborative countries, authorship pattern, top authors, cocitation networks and assorted facets.\u0000\u0000\u0000Design/methodology/approach\u0000Web of Science database was used to retrieve the required data for this study. Keeping the objectives of this study in mind, the keyword “Digital Divide” was used as the search term. Moreover, the retrieved data were limited from the year 2001 to 2020 for two decades. A total of 5,518 publications were filtered and focused for subsequent facet-wise analysis and interpretation. Required bibliometric indicators like types of documents, yearly growth, authorship pattern, degree of collaboration (DC), country productivity, h-index and citation impact were used to study various dimensions of publication trends. VOSviewer software was used to visualize the authorship network, bibliographic coupling and keyword occurrences.\u0000\u0000\u0000Findings\u0000This study finds a total of 5,518 publications on the topic digital divide contributed by 14,277 authors from 130 countries across the world published through 2,843 source titles in 13 global languages during the past two decades (2001–2020). The annual growth of publications (AGP) on the topic digital divide shows 38.43% AGP globally. Journal articles have been identified as the preferred type of document with 73.11% of the literature. The DC indicates a healthy trend of collaborative research with a mean value of 0.70. The USA is the table topper with the contribution of 1,933(35.03%) publications and 77 h-index and James J., from Tilburg University, The Netherlands, is identified as top amongst the most productive authors with the highest number of 34 publications (h-index 14).\u0000\u0000\u0000Research limitations/implications\u0000This study restricts its scope on research productivity to the theme “digital divide” regarding authorship pattern, DC, most productive authors, most productive countries, most published sources and other key facets. This study exclusively refers to the Web of Science database in retrieving the required data. Moreover, this study takes global research into account with no geographical or language limitations and comprehends literature on digital divide for two decades ranging from the years 2001 to 2020.\u0000\u0000\u0000Practical implications\u0000Teachers and research scholars interested in bibliometric studies can benefit from insights into the scholarly documents published on the topic digital divide from 2001 to 2020.\u0000\u0000\u0000Originality/value\u0000This study yields some interesting findings on published literature on the digital divide during the past two decades relating to the most striking contributions, highly cited journals, the most prolific authors, country productivity, keyword cooccurre","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90595819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-07-2022-0180
A. Singla, R. Agrawal
Purpose This paper aims to propose DisDSS: a Web-based smart disaster management (DM) system for decision-making that will assist disaster professionals in determining the nature of disaster-related social media (SM) messages. The research classifies the tweets into need-based, availability-based, situational-based, general and irrelevant categories and visualizes them on a web interface, location-wise. Design/methodology/approach It is worth mentioning that a fusion-based deep learning (DL) model is introduced to objectively determine the nature of an SM message. The proposed model uses the convolution neural network and bidirectional long short-term memory network layers. Findings The developed system leads to a better performance in accuracy, precision, recall, F-score, area under receiver operating characteristic curve and area under precision-recall curve, compared to other state-of-the-art methods in the literature. The contribution of this paper is three fold. First, it presents a new covid data set of SM messages with the label of nature of the message. Second, it offers a fusion-based DL model to classify SM data. Third, it presents a Web-based interface to visualize the structured information. Originality/value The architecture of DisDSS is analyzed based on the practical case study, i.e. COVID-19. The proposed DL-based model is embedded into a Web-based interface for decision support. To the best of the authors’ knowledge, this is India’s first SM-based DM system.
{"title":"DisDSS: a novel Web-based smart disaster management system for determining the nature of a social media message for decision-making using deep learning – case study of COVID-19","authors":"A. Singla, R. Agrawal","doi":"10.1108/gkmc-07-2022-0180","DOIUrl":"https://doi.org/10.1108/gkmc-07-2022-0180","url":null,"abstract":"\u0000Purpose\u0000This paper aims to propose DisDSS: a Web-based smart disaster management (DM) system for decision-making that will assist disaster professionals in determining the nature of disaster-related social media (SM) messages. The research classifies the tweets into need-based, availability-based, situational-based, general and irrelevant categories and visualizes them on a web interface, location-wise.\u0000\u0000\u0000Design/methodology/approach\u0000It is worth mentioning that a fusion-based deep learning (DL) model is introduced to objectively determine the nature of an SM message. The proposed model uses the convolution neural network and bidirectional long short-term memory network layers.\u0000\u0000\u0000Findings\u0000The developed system leads to a better performance in accuracy, precision, recall, F-score, area under receiver operating characteristic curve and area under precision-recall curve, compared to other state-of-the-art methods in the literature. The contribution of this paper is three fold. First, it presents a new covid data set of SM messages with the label of nature of the message. Second, it offers a fusion-based DL model to classify SM data. Third, it presents a Web-based interface to visualize the structured information.\u0000\u0000\u0000Originality/value\u0000The architecture of DisDSS is analyzed based on the practical case study, i.e. COVID-19. The proposed DL-based model is embedded into a Web-based interface for decision support. To the best of the authors’ knowledge, this is India’s first SM-based DM system.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83698477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-11-2022-0254
Hossein Motahari-Nezhad
Purpose The use of social media is one of the new technological options that has been recommended as a potential new strategy for delivering high-quality, high-value cancer prevention and management services. Despite the increasing use of social media, little research has been done on the use of social media in brain tumors. Therefore, this systematic review aims to provide a comprehensive review of the use of social media in brain tumor research. Design/methodology/approach A systematic search was performed in PubMed, Scopus and Web of Science from inception to August 1, 2022. English full-text articles evaluating social media use, benefit or content in brain tumor were considered. Findings Sixteen documents satisfied the inclusion criteria and were included in the final analysis. Most of the included studies (n = 11/16) were conducted and published by researchers in the USA. In terms of social media platform, most studies focused on Twitter (8/16, 50%) and YouTube (8/16, 50%), followed by Facebook (6/16, 37.5%) and Instagram (4/16, 25%). Most studies (n = 7/12) analyzed the content of brain tumor information provided on social media, followed by patients’ use of social media (n = 3/12) and the quality of information on social media (n = 3/12). The other three articles also examined patient recruitment, crowdfunding and caregiver use of social media. Practical implications By identifying the use, benefits and content of social media platforms in different settings, patients, clinicians and policymakers can better benefit from harnessing the power of social media in different ways, leading to improved health-care services. Originality/value To the authors knowledge, this is the first study to systematically examine social media use, benefits and content status in brain tumors.
{"title":"A systematic review of the available literature on the use of social media in brain tumor","authors":"Hossein Motahari-Nezhad","doi":"10.1108/gkmc-11-2022-0254","DOIUrl":"https://doi.org/10.1108/gkmc-11-2022-0254","url":null,"abstract":"\u0000Purpose\u0000The use of social media is one of the new technological options that has been recommended as a potential new strategy for delivering high-quality, high-value cancer prevention and management services. Despite the increasing use of social media, little research has been done on the use of social media in brain tumors. Therefore, this systematic review aims to provide a comprehensive review of the use of social media in brain tumor research.\u0000\u0000\u0000Design/methodology/approach\u0000A systematic search was performed in PubMed, Scopus and Web of Science from inception to August 1, 2022. English full-text articles evaluating social media use, benefit or content in brain tumor were considered.\u0000\u0000\u0000Findings\u0000Sixteen documents satisfied the inclusion criteria and were included in the final analysis. Most of the included studies (n = 11/16) were conducted and published by researchers in the USA. In terms of social media platform, most studies focused on Twitter (8/16, 50%) and YouTube (8/16, 50%), followed by Facebook (6/16, 37.5%) and Instagram (4/16, 25%). Most studies (n = 7/12) analyzed the content of brain tumor information provided on social media, followed by patients’ use of social media (n = 3/12) and the quality of information on social media (n = 3/12). The other three articles also examined patient recruitment, crowdfunding and caregiver use of social media.\u0000\u0000\u0000Practical implications\u0000By identifying the use, benefits and content of social media platforms in different settings, patients, clinicians and policymakers can better benefit from harnessing the power of social media in different ways, leading to improved health-care services.\u0000\u0000\u0000Originality/value\u0000To the authors knowledge, this is the first study to systematically examine social media use, benefits and content status in brain tumors.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83712531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-07-2022-0156
A. Singla, R. Agrawal
Purpose This study aims to propose a novel deep learning (DL)-based framework, iRelevancy, for identifying the disaster relevancy of a social media (SM) message. Design/methodology/approach It is worth mentioning that a fusion-based DL model is introduced to objectively identify the relevancy of a SM message to the disaster. The proposed system is evaluated with cyclone Fani data and compared with state-of-the-art DL models and the recent relevant studies. The performance of the experiments is assessed by the accuracy, precision, recall, f1-score, area under receiver operating curve and precision–recall curve score. Findings The iRelevancy leads to a better performance in accuracy, precision, recall, F-score, the area under receiver operating characteristic and area under precision-recall curve, compared to other state-of-the-art methods in the literature. Originality/value The predictive performance of the proposed model is illustrated with experimental results on cyclone Fani data, along with misclassifications. Further, to analyze the performance of the iRelevancy, the results on other cyclonic disasters, i.e. cyclone Titli, cyclone Amphan and cyclone Nisarga are presented. In addition, the framework is implemented on catastrophic events of different natures, i.e. COVID-19. The research study can assist disaster managers in effectively maneuvering disasters during distress.
{"title":"iRelevancy: a framework to identify the relevancy of a social media message to a disaster","authors":"A. Singla, R. Agrawal","doi":"10.1108/gkmc-07-2022-0156","DOIUrl":"https://doi.org/10.1108/gkmc-07-2022-0156","url":null,"abstract":"\u0000Purpose\u0000This study aims to propose a novel deep learning (DL)-based framework, iRelevancy, for identifying the disaster relevancy of a social media (SM) message.\u0000\u0000\u0000Design/methodology/approach\u0000It is worth mentioning that a fusion-based DL model is introduced to objectively identify the relevancy of a SM message to the disaster. The proposed system is evaluated with cyclone Fani data and compared with state-of-the-art DL models and the recent relevant studies. The performance of the experiments is assessed by the accuracy, precision, recall, f1-score, area under receiver operating curve and precision–recall curve score.\u0000\u0000\u0000Findings\u0000The iRelevancy leads to a better performance in accuracy, precision, recall, F-score, the area under receiver operating characteristic and area under precision-recall curve, compared to other state-of-the-art methods in the literature.\u0000\u0000\u0000Originality/value\u0000The predictive performance of the proposed model is illustrated with experimental results on cyclone Fani data, along with misclassifications. Further, to analyze the performance of the iRelevancy, the results on other cyclonic disasters, i.e. cyclone Titli, cyclone Amphan and cyclone Nisarga are presented. In addition, the framework is implemented on catastrophic events of different natures, i.e. COVID-19. The research study can assist disaster managers in effectively maneuvering disasters during distress.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84343988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/gkmc-12-2022-0287
Shinichi Yamaguchi, Tsukasa Tanihara
Purpose In recent years, the social impact of misinformation has intensified. The purpose of this study is to clarify the mechanism by which misinformation spreads in society. Design/methodology/approach Testing the following two hypotheses by a logit model analysis of survey data using actual fact-checked COVID-19 vaccine and political misinformation: people who believe that some misinformation is true are more likely to spread it than those who do not believe in its truthfulness; people with lower media and information literacy are more likely to spread misinformation than people with higher media and information literacy. Findings The two hypotheses are supported, and the trend was generally robust regardless of the method, whether the means of diffusion was social media or direct conversation. Social implications The authors derived the following four implications from the results: governments need to further promote media information literacy education; platform service providers should consider mechanisms to facilitate the spread and display of posts by people who are aware of misinformation; fact-checking should be further promoted; people should acquire information based on the assumption that people who believe in some misinformation tend to spread it more. Originality/value First, it quantitatively clarifies the relationship between misinformation, true/false judgements and dissemination behaviour. Second, it quantitatively clarifies the relationship between literacy and misinformation dissemination behaviour. Third, it conducts a comprehensive analysis of diffusion behaviours, including those outside of social media.
{"title":"Relationship between misinformation spreading behaviour and true/false judgments and literacy: an empirical analysis of COVID-19 vaccine and political misinformation in Japan","authors":"Shinichi Yamaguchi, Tsukasa Tanihara","doi":"10.1108/gkmc-12-2022-0287","DOIUrl":"https://doi.org/10.1108/gkmc-12-2022-0287","url":null,"abstract":"Purpose In recent years, the social impact of misinformation has intensified. The purpose of this study is to clarify the mechanism by which misinformation spreads in society. Design/methodology/approach Testing the following two hypotheses by a logit model analysis of survey data using actual fact-checked COVID-19 vaccine and political misinformation: people who believe that some misinformation is true are more likely to spread it than those who do not believe in its truthfulness; people with lower media and information literacy are more likely to spread misinformation than people with higher media and information literacy. Findings The two hypotheses are supported, and the trend was generally robust regardless of the method, whether the means of diffusion was social media or direct conversation. Social implications The authors derived the following four implications from the results: governments need to further promote media information literacy education; platform service providers should consider mechanisms to facilitate the spread and display of posts by people who are aware of misinformation; fact-checking should be further promoted; people should acquire information based on the assumption that people who believe in some misinformation tend to spread it more. Originality/value First, it quantitatively clarifies the relationship between misinformation, true/false judgements and dissemination behaviour. Second, it quantitatively clarifies the relationship between literacy and misinformation dissemination behaviour. Third, it conducts a comprehensive analysis of diffusion behaviours, including those outside of social media.","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135583262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-27DOI: 10.1108/gkmc-09-2022-0215
M. Saxena, Dharmesh K. Mishra
Purpose Employee engagement (EE) can result in multiple positive impacts not only on the individual and his/her team but also on the organisational and financial outcome of the business. If artificial intelligence (AI) can be used as a tool to facilitate EE, organisations will be more than satisfied to adopt it. The paper aims to study the penetration of AI for EE in corporate India. Design/methodology/approach Based on the information gathered through secondary research, a framework of questions was built and sent to some senior people in the area of AI and HR to check for its completeness. Respondents based on inclusion criteria were selected through random purposive sampling to be a part of the study. A total of 23 respondents participated in the study. Qualitative data analysis of the transcripts was conducted using MAXQDA 2022 (Verbi Software, Berlin, Germany), which is a qualitative data analysis software. Multiple readings were undertaken to identify the patterns and relationships in the data. Findings The participants described a variety of issues while using or planning to use AI for EE. Some of the issues mentioned were related to cost, challenges, mindsets and attitudes, demography of employees, comfort in the use of technology, size of the organisation, change management strategies, software vendors and vendor support. The most common responses were grouped into headings such as Organisation, Process, Employee and Software Choice Related aspects. Originality/value Lately, the overall work environment, work and personal life balance, and quality of life have become more desirable than earning a good salary. AI is becoming a part of various aspects of business but its role in HR is yet to be explored. AI’s capabilities to predict may result in more employee work satisfaction. The paper explores the possibility of using AI as a tool in every aspect of employee life cycle, thereby attempting to make HR processes more productive and enhance EE.
{"title":"Artificial intelligence: the way ahead for employee engagement in corporate India","authors":"M. Saxena, Dharmesh K. Mishra","doi":"10.1108/gkmc-09-2022-0215","DOIUrl":"https://doi.org/10.1108/gkmc-09-2022-0215","url":null,"abstract":"\u0000Purpose\u0000Employee engagement (EE) can result in multiple positive impacts not only on the individual and his/her team but also on the organisational and financial outcome of the business. If artificial intelligence (AI) can be used as a tool to facilitate EE, organisations will be more than satisfied to adopt it. The paper aims to study the penetration of AI for EE in corporate India.\u0000\u0000\u0000Design/methodology/approach\u0000Based on the information gathered through secondary research, a framework of questions was built and sent to some senior people in the area of AI and HR to check for its completeness. Respondents based on inclusion criteria were selected through random purposive sampling to be a part of the study. A total of 23 respondents participated in the study. Qualitative data analysis of the transcripts was conducted using MAXQDA 2022 (Verbi Software, Berlin, Germany), which is a qualitative data analysis software. Multiple readings were undertaken to identify the patterns and relationships in the data.\u0000\u0000\u0000Findings\u0000The participants described a variety of issues while using or planning to use AI for EE. Some of the issues mentioned were related to cost, challenges, mindsets and attitudes, demography of employees, comfort in the use of technology, size of the organisation, change management strategies, software vendors and vendor support. The most common responses were grouped into headings such as Organisation, Process, Employee and Software Choice Related aspects.\u0000\u0000\u0000Originality/value\u0000Lately, the overall work environment, work and personal life balance, and quality of life have become more desirable than earning a good salary. AI is becoming a part of various aspects of business but its role in HR is yet to be explored. AI’s capabilities to predict may result in more employee work satisfaction. The paper explores the possibility of using AI as a tool in every aspect of employee life cycle, thereby attempting to make HR processes more productive and enhance EE.\u0000","PeriodicalId":43718,"journal":{"name":"Global Knowledge Memory and Communication","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73364289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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