International Journal of Information Science and Management (IJISM)

Abstract  Digital Libraries have emerged as an essential component of worldwide information infrastructure, adopting the latest Information and Communication Technology (ICT) to promote an organizational structure that encourages communication and resource sharing between academicians and researchers across the countries. The study explored global digital library literature that has been carried out in the years 2007-2021 based on various scientometric indicators such as publication output, prolific author, collaboration network by author, productive institution, and country. The key term "digital library" was used in our search strategy from the Web of Science. The data was saved and imported into R Studio and VOS viewer for analysis and illustration of our data. We accessed 5855 records retrieved from the Web of Science. The United States had the most documents published, followed by China and England. The journals of Electronic Library were ranked first. The University of California System was the top organization with many scientific publications with 5549 citations. This research gives scholars and practitioners a thorough overview of the key research issues and trends in digital library research worldwide. Digital libraries worldwide have impacted the research society. It is an extension of a physical library into an electronic library. This study is very significant in the current scenario to know the global growth rate of scientific literature.

Abstract  The number of papers and scientific productions published in journals indexed in indexing/abstracting databases is used as a measure of the growth of science. One of the reasons for the ability of the Islamic Republic of Iran in various fields can be attributed to the scientific growth of Iran in recent years. This survey used scientometric approaches for measuring the scientometric indicators at hand. The research population included all papers authored by Iranians indexed in Web of Science (WOS) from 1980-2021.  Accordingly, in this research, the quantitative growth of Iranian science during the four decades after the Islamic Revolution of Iran (by counting the number of indexed papers in the Web of Science) and the factors affecting the growth of Iranian science are examined. Factors such as the growth in the number of faculty members, the growth in the number of graduate students, the promotion regulations of the Ministry of Science, Research and Technology (MSRT) and the Ministry of Health, and Medical Education (MHME) along with encouraging policies for scientific production in Iran and the comprehensive scientific map of the country, Scientific research towards the needs and priorities of the country, the graduation regulations of graduate students, other social, political, cultural and international factors analyzed. The results of the four decades of Iran's science production showed that the highest amount of Iran's science production, i.e., more than 75% of Iran's science production, occurred in the fourth decade (2011-2021). In general, in the second period (2001-2021), the relationship between academic degrees and science production is significantly higher than in the first period (1980-2000).  In 2023, Iran will be the fourth largest producer of nanoscience in the world with 7.30 percent of the world's science production in the field of nanoscience, and countries such as Japan, South Korea, Germany, France, England, and Italy are after Iran. The results of analysis and investigation of the research also showed that the number of graduates at both master's and doctorate levels, as well as the population of full-time faculty members of the universities, were proportional with the production of Iranian science in these years There has been an increasing trend from 1980 to 2021. Despite the ups and downs of the share of research in the gross national product in Iran, which has always decreased and was less than one percent, the growth of science in Iran has been on an upward trend. According to the number of Iranian scientific publications in the WOS database at the end of 2021, which has reached 56,000, it seems that due to the growth of Iran's scientific productions, we can hope that the number of Iranian scientific publications will reach 2026 (1404) by the end of the Horizon program has arrived.
 

Abstract  
This study aimed to investigate the attention given to scientific outputs about COVID-19 vaccines worldwide on social media. It utilized scientometrics and altmetrics indicators. A dataset with 12,364 works indexed in the WOS database from 2020 to 2022 was analyzed. Altmetric Scores (AS) and Altmetrics were extracted from Altmetric Explorer. Data analysis was performed using Access, Excel, and SPSS software. The retrieved articles garnered attention on 13 social media platforms.  The highest amount of social attention, accounting for 97% of the total, was related to X (Twitter) and Mendeley. The highest AS (43,765) was for an open-access article entitled "Covid-19: Researcher blows the whistle on data integrity issues in Pfizer's vaccine trial: Video 1" in the BMJ cited in 14 social media. The most productive countries in COVID-19 vaccine research were the USA, England, and China, while Harvard University, the University of London, and the University of California emerged as the most active research institutes. The findings confirmed a significant, moderate, and positive correlation between the AS and most Altmetrics with the number of citations. Additionally, a positive, substantial, and moderate correlation was observed between citations, the AS of highly-cited papers, and the AS of hot documents. Considering the positive impact of social media on increasing the chance of receiving more citations for articles and improving the impact range of articles from academic users to social users, the activities of researchers in social media are effective in increasing the visibility of scientific works.
 
 

Abstract This research aims to examine the nuclear fusion technology field using the intellectual structure drawing technique. It is worth mentioning that the reason for focusing on this area, atomic fusion, is its peaceful applications and unlimited fuel to generate power. The proposed strategy in this paper includes all the keywords related to the research topic. VOS viewer and R Studio software were employed for data analysis. In addition, the principal research topics were extracted and classified using scientific maps. This analysis indicates the intellectual structure of the topic, which is grouped into four fundamental clusters using citation networks. This study additionally identifies emerging issues and future research directions implementing strategic diagrams. Another aspect of this study that reveals the intellectual foundation of the research is that it provides insights into the importance of crucial topics, institutions, and publications in terms of the field's focus and the results obtained from the analysis of the period 1991-2023. It informs that the conceptual evolution of nuclear fusion and its growth is proceeding.
 

Abstract  
The present study aims to analyze the acceptance times of scientific papers presenting bibliometric analyses of COVID-19 literature published in the first phase of the pandemic. We collected the data from the Web of Science of Clarivate Analytics. The analysis considered various aspects of the papers and the published journals, such as document type, impact factor (IF) quartile rank of journals, and journal indexation. An initial search yielded 149 papers, 91 of which were selected for further analysis after excluding editorial materials and articles unrelated to COVID-19 and bibliometrics. We should have collected the required submission history information for fourteen of the 91 papers. The analysis revealed that acceptance times of bibliometric analyses on COVID-19 literature ranged between 1 and 238 days, with a median of 47 and a mean of 66.4 days. Most papers had shorter acceptance times than the mean, with only a few documents being accepted after a long wait. Journals without IF had lower acceptance times than those with IF, whereas journals with an IF between 2 and 2.99 had the most extended acceptance times; similarly, second- and fourth-quartile journals had a shorter acceptance time for papers than first- and third-quartile journals. Journals indexed in ESCI accepted documents in less time than journals indexed in other databases. In conclusion, scientific journals joined the rush to publish COVID-19-related research, as they shortened acceptance times for bibliometric analyses on COVID-19 literature published during the first phase of the pandemic compared to the period before the pandemic.
 

Abstract  This research investigates the impact of database quality, reputation, credibility, and comprehensiveness on graduate students' information use with the mediating role of empowerment at Shahid Chamran University of Ahvaz. The design of the study is descriptive-causal. The research instrument is a questionnaire. Cronbach's test was used to check the reliability of the questionnaire. The results of this test were equal to 0.842, which showed the excellent reliability of the questionnaire. The research population included all graduate students (N= 5137) of the Shahid Chamran University of Ahvaz. Research sample (N=358) graduates were selected based on Krejcie and Morgan’s table via random sampling. The results showed that the quality of database resources has a positive and significant effect on the use of database resources among the Shahid Chamran University of Ahvaz graduate students. In addition, the reputation of database resources has a positive and significant effect on the use of database resources. The results also indicated a positive and significant effect of resource validity on the use of information resources. Furthermore, the comprehensiveness of resources positively and significantly affected the graduates' receipt, use, and ability to use resources. Finally, the implications suggest that the quality of information resources on the receipt and use of information affect the comprehensiveness of information resources and the use of resources mediated.
 

Abstract This research analyzes the criteria of academic staff members of Shahid Bahonar University for valuing information as an asset. The research method is a descriptive survey, and the statistical population of the research is the faculty members of the Shahid Bahonar University of Kerman. The data collection tool was a researcher-made questionnaire, and the validity of the questionnaire was confirmed by experienced professors and experts from Cronbach's alpha, which was calculated as 0.764. Data was analyzed using SPSS version 23 software descriptive statistics and one-sample t-tests, and Friedman was used. The findings showed that in the Shahid Bahonar University of Kerman, the criteria of the number of scientific productions leading to the development of knowledge, the number of scientific productions leading to the development of the organization's goals, and the number of scientific productions leading to effectiveness using the value of productivity, the criterion of paying the subscription fee to use Databases are valued with the information use value index. No measures of information are valued with the exchange value index. Based on the Friedman test, the criteria of "value of paying a fee to meet information, educational and research needs," "credit value of paying a fee to meet information, educational and research needs," and "value of paying a fee in influential databases to meet information needs, Educational and Research" are in the first to third categories respectively. What is obtained from the results of this research is that in three important and influential areas of productivity, use of information, and exchange value of information, faculty members pay the most attention to the issues related to the production of information for the development of knowledge and organization, as well as the cost of information consumption and the value of information. They are aimed at payment.

Abstract  This study examines scientific productivity in Middle Eastern (ME) countries within the discipline of Library and Information Science (LIS) for the entire period for which data is available, 1979-2023. The productivity of ME countries in all document types was only 1.49% under the LIS research area. Although academic productivity has increased considerably over the years, the contribution of ME researchers to global LIS discourse remains limited. The five most productive ME countries in LIS are Turkey (23rd), Iran (26th), Israel (31st), Saudi Arabia (42nd), and United Arab Emirates (46th). While Israel ranks the highest for international collaboration, institutions in Iran and Turkey are more likely to cooperate at national levels. Articles in the field of LIS were found to be highly related to computer science (f: 1894), business economics (f: 612), and health-related research fields (f: 206). In addition, knowledge management, social media, academic libraries, information retrieval, Internet, e-government, and bibliometrics were the most intensively studied topics. The study is crucial to appreciate the general situation of the LIS field in a region containing cities that have hosted the largest libraries in history (such as Alexandria and Beytü'l-Hikme). The Middle East has an important heritage for library and information science and this study’s findings open the discussion of how the region can perform better. Policymakers and those developing higher education policies in the region should emphasize infrastructure development, public awareness, education, research and academic programs, international and regional cooperation, policy, and support for collaboration and sharing.
 
 

Abstract  The aerospace industry and technology are always considered one of the country’s most important and valuable industries. The research area of "Aerospace" is among the priorities of the grand science and technology development strategies, and addressing it is strategically vital. The present research aims to estimate and predict the appropriate algorithm for identifying high-quality aerospace researchers based on Advanced Ensemble Classifier Techniques (AECT) in data mining on the outputs of scientometric analyses and predicting the most essential scientometric-related metrics to identify high-quality researchers. The present study was performed using the protocols of applied research and multiple methods. The studied population includes all aerospace researchers (1945 and 2021) indexed in "The Web of Science Core Collection (WOSCC)". DataLab software and multiple programming languages have been applied in this research. All three algorithms have an accuracy of 0.96 and an F1-score of 0.97, which indicates that the models have high accuracy, validity, sensitivity, and predictive power. The "Blending" algorithm is considered a suitable and predictive model. The output of the LightGBM algorithm is that the most important and robust metric in the evaluation of prominent researchers is a metric from the researchers' effectiveness dimension, the Q parameter. According to the knowledge obtained from the ability to predict AECT in the prediction of high-quality researchers, it is possible to use the metrics mentioned in the evaluation of researchers in the field of scientometrics for more accurate and comprehensive prediction. An algorithm that can lead to the optimal and efficient classification of researchers provides the possibility of in-depth analysis of the available data about researchers and smooths the predictive power of the most high-quality researcher. The use of the proposed algorithms in this research, while suggesting the appropriate algorithm, led to reliable and valuable knowledge in classifying high-quality aerospace researchers.

Abstract  This study investigated the effects of computer self-efficacy, computer literacy skills, and cognitive skills on the use of electronic resources among social science doctoral students in Nigerian federal universities. The methodology adopted was the survey research design of the correlational type and a stratified random sampling technique was used to select 2,108 from the population size of 3,342 in 33 faculties of social sciences. Results of the research revealed that there were significant relationships among computer self-efficacy, computer literacy skills, and cognitive skills on the use of electronic resources among social science doctoral students. Computer self-efficacy, computer literacy skills, and cognitive skills have a significant joint effect on the use of electronic resources among Social Science doctoral students in Nigerian Federal Universities. It was therefore recommended that curriculum upgrades be done from undergraduate to postgraduate level that will inculcate the use of computers for learning and various presentations to enhance computer self-efficacy, computer literacy skills, and cognitive skills of doctoral students.

Abstract  
In crises, people usually experience uncertainty and seek information to solve and share that information. One of the recent crises was COVID-19. The present study aimed to study the information behavior (Information-Seeking, Information sharing, Media Credibility) during the COVID-19 crisis. A descriptive quantitative research design was employed. Data for this research was collected through a questionnaire from 1,073 Iranian individuals. Cluster sampling was used, and participants were selected using snowball sampling. The findings showed that the first three media to access information during the COVID-19 crisis were Internet news sites, social networks, and traditional news media (TV, newspapers, etc.). The first three media for sharing information were phone conversations with acquaintances and friends, groups in social networks, and face-to-face information sharing with acquaintances and friends. Also, TV and social networks are the most trusted media for receiving information among participants who prefer to believe the information provided by the mass media when they have a conflict in choosing between the information received between mass media and interpersonal channels. Generally, during the COVID-19 crisis, participants obtained more information from official and government information sources, but they shared information through social networks and phone calls. Also, when there is a conflict to choose between information channels, they tend to use mass media such as TV rather than personal channels. Also, in terms of orientation to information, they did not seek more information, did not avoid the obtained and existing information, and did not show apprehension.
 

Abstract Social Media Marketing (SMM) has impacted marketing significantly in the past decade. This study uses bibliometric and content analysis to examine academic research on Social Media Marketing (SMM). Focusing on the Scopus database, the research analyzed 899 papers from 2011 to 2021, excluding duplicates. We employed performance analysis, science mapping, and content analysis to understand social media marketing comprehensively. The top journal publishing SMM papers was the Journal of Interactive Marketing, with 6424 citations and 41 articles. The most influential author was Hollebeek L D..Science mapping revealed that ‘"influencer marketing",’ ‘"social media advertising,"’ and ‘"social media"’ are the trending themes in SMM. These themes complement the results found in co-citation clusters. Future research should use new theoretical frameworks like the Consumers Online Brand Related Activities (COBRA) Framework and apply Pierre Bourdieu's social capital theory in the context of SMM. This study offers a comprehensive understanding of social media marketing by visualizing the latest fields of research and trending themes. This study identifies various strategies used in social media marketing and how marketers can garner high engagement. This study utilizes various bibliometric methods to deliver a broad view of social media marketing and content analysis. The latest trends in the field are identified through science mapping techniques. Further, it also gives insight into the top authors and journals that prominently publish literature on social media marketing.
 

Abstract  Science, technology, and innovation policy-making laboratories, by providing policymakers with educational, research, and consulting services, before the introduction of policy recommendations to the regulatory and legal structures, make it possible to test the policies on a small scale. Thus, the waste of huge resources allocated to the development of political solutions and additional damages may be prevented. On the other hand, future research as a process gives a more complete understanding of the forces of the long-term future, which should be taken into account in developing policy-making, planning, and decision-making. Therefore, future research of science, technology, and innovation policy-making laboratories to synchronize with today's world and for optimal policies is a necessity addressed in the present study. This study was applied in terms of objective and mixed in terms of method (literature review). In this survey, experts' opinions, interaction analysis, and scenarios have been used. The approach of the present study was future research. For data analysis, the SPSS, MicMac, and ScenarioWizard were used. The statistical population included a group of experts in the field of science, technology, and innovation policy-making. The analysis of data related to different states using ScenarioWizard showed that the probability of occurrence of 9 scenarios was more than other scenarios and the probability of occurrence of other 297 scenarios was very small and weak. The initial review of the scenarios showed the relative dominance of static state over desired and critical states. Out of 9 scenarios, 4 scenarios were strong and more probable. Scenario 1 with an impact score of 221 was the strongest, most desired, and most probable scenario facing science, technology, and innovation policy-making laboratories. Scenario 2 with an impact score of 181 was one of the most desired and probable scenarios facing science, technology, and innovation policy-making laboratories. Scenario 3 had an impact score of 102. Under this scenario, 4 key influencing driving forces were desired and 8 key influencing driving forces were static. Scenario 4 had an impact score of 65. Under this scenario, 8 key influencing driving forces were static and 4 key influencing driving forces were undesired.
 
 

Abstract  Despite the importance of Marketing Intelligence (MI) and the Internet of Things (IoT), Customer Relationship Management (CRM), and Customer Experience Management (CEM) in the competitive context, more research on the integration of these concepts for sustained competitive advantage is necessary. Thus, Snow Company must effectively utilize these concepts to establish a sustained competitive advantage. Therefore, this study investigates the impact of IoT, CRM, CEM, and MI on attaining sustained competitive advantage. By employing a structural equation model and Smart-PLS software, we analyzed data collected from 186 managers and employees of Snowa Company. Our findings indicate that integrating IoT, CRM, and CEM concepts into marketing intelligence is the most beneficial strategic approach for achieving sustained competitive advantage for Snowa Company. Through this integration, company managers can enhance their marketing and innovation capabilities, strengthen strategic solutions, and achieve sustained competitive advantage.

Abstract  Recent developments in emerging technologies have enabled users to interact with social networks. Nowadays, one of the ways of interaction is to understand the real feelings of people at the moment, the outcome of which, based on the people’s reaction and attitude, appears in analyzing feelings like facial features, type of speech, or the people’s jobs such as video, photograph, voice, and text. In this research, through deep learning and machine learning in the AI, the sentiment analysis has been studied and evaluated using AI and deep learning algorithms like motion detection, body language recognition, image processing, sound and text processing, computer vision, natural language processing and different network techniques. The paper, providing a new conceptual model design, has provided more details about sentiment analysis in social networks by incorporating AI techniques in social networks with high speed and accuracy.
 

Abstract  
 One of the new approaches to organizing journal articles is using Semantic Web technologies and new "Semantic Publishing" methods based on the ontological models for semantic modeling and representation of these publications. This study aims to design the metadata ontology model for semantic modeling and representation of scholarly journal articles. This research was carried out using the content analysis method. The study population includes articles published in ISC journals (i.e., journals indexed in ISC). A sample of 200 articles from a Persian journal (i.e., "Iranian Journal of Information Processing & Management") and an English journal (i.e., "International Journal of Information Science and Management (IJISM)") were considered for semantic modeling and representation using the metadata ontology model. The data-gathering method was a systematic observation, and the data-gathering tool was a checklist based on the Semantic Publishing and Referencing Ontologies (SPAR Ontologies). This research identified the metadata entities required for semantic modeling and representation of ISC scholarly journal articles. Then, the metadata ontology model was designed using Protege (an ontology editor) and the RDF representation of the model was created in RDF/XML Syntax. After designing the metadata ontology model, the RDF graph of this model was developed to analyze the entities and relationships between them, and its results were analyzed. The results of RDF graph analysis show that the design of the ontology model and the creation of the RDF links between entities significantly impact the semantic description and representation of metadata entities of the ISC scholarly journal articles and the network of relations between them.