International Journal of Information Science and Management
Volume:21 Issue: 1, Winter 2023

The altmetric Attention Score scale quantifies the attention that publications receive on various social media. Some studies have been conducted on the correlation between AAS and citations of articles in other disciplines but orthopedics. This study aimed to compare AAS with citation numbers on the top 50 articles regarding citation numbers. For this study the Scopus database was searched for the most 50 cited manuscripts on orthopedics from January 2015 to December 2020. Subsequently, altimetric attention score (AAS) and the number of Tweeters, Dimensions, etc, were retrieved for each article through "Bookmarklet for Researchers" at Altmetric.com. Results show a statistically low and non-significant relationship was indicated between the citation number and the AAS and also shown the linear relationship between the mention on Twitter and the altmetric attention score.  Most of previous articles represented that there is a weak to moderate relationship between the citation number and the AAS that is similar to our findings. There is a low but significant correlation exists between the AAS and the number of citations. In addition, the AAS is directly and linearly linked to the number of mentions on Twitter.

Safety and health are intricately interwoven and have become indispensable to the thriving business world and anthropology. It is concerned with ensuring employees’ physical, emotional, and mental well-being. Based on the Scopus and Web of Science databases, the current study intends to analyse the global research output on machine learning in safety and health. This study utilized ScientoPy and VOSviewer to delve into the annual growth, patterns of research communication on source titles, international collaboration among countries, and authors’ keyword analysis. This study found that the Web of Science database tracks the evolution of publications throughout time. PLoS One has surpassed all other source titles in terms of publishing activity. Also, this study indicated that US researchers are constantly working on machine learning in safety and health research and have developed significant collaborations with China and Australia. Between 2020 and 2021, the University of Toronto published 86% of all papers, outpacing other institutions.  The keywords “machine learning”, “artificial intelligence”, “electronic health records”, “deep learning”, and “mental health” were the most popular and trending keywords in 2020 and 2021, and “artificial intelligence” appeared in most publications among others. Future researchers should conduct scoping or systematic literature reviews to elucidate the relationships between these terms. This study may entice the curiosity of practitioners and researchers to advance new knowledge in this field by being devoted to cutting-edge research in the contemporary philosophy of science, cognitive, and cultural anthropology on machine learning in safety and health research. In conclusion, this scientometric analysis demonstrates that machine learning in safety and health is a study domain that requires further refinement in future research, as this technology has the potential to significantly improve workplace safety and health through targeted applications with clear benefits.

The research aims to visualize and analyze the co-word network and thematic clusters of the intellectual structure in gas turbine thermal management during 1919-2020. The study is applied research in terms of the purpose, which is conducted with a descriptive approach, scientometrics indicators, techniques of co-word, and social network analysis. Data analysis and visualization of the co-word network were represented by VoS Viewer, SPSS, UCINet, and python Software. The top scientific products in the last century were related to engineering subject area and published by the USA country. Seven main clusters were identified for the index keywords, and 20 main clusters were recognized for the author keywords in Scopus regarding the network structure and thematic clusters based on the co-occurrences. Moreover, 38 clusters were identified based on the hierarchical clusters. The clusters, namely heat flux calculations and radiation effects, thermal performance optimization, and operational considerations, have central and major positions in this field and have more potential to maintain and develop themselves in the future. The future of Research and Development (R&D) activities in the area will be focused on novel cycles, heat map development, and Techno-Economic and Risk Analysis (TERA) by utilizing systematic approaches for the identification of heat sinks and sources, fluid modeling, and environmental considerations. In addition, the emerging contributors in the field will be advanced manufacturing and material considerations.

This study aims to perform a bibliometric analysis of documents published in the field of Public Administration during the years 1923-2020. In this bibliometric study, all Web of Science (WOS) databases were used to retrieve the publications in this field. Using a proper search strategy, 93093 records were retrieved in the WOS database from 1923 to 2020. Excel and VOSviewer software were used for bibliometric analysis and visualization of documents. The findings show that 64.31% of documents (59860 documents) were articles; most documents were published in the Public Administration Review-Journal (n= 9011). The United States (with 31930 documents), ENGLAND (with 14636 documents), and Canada (with 7104 documents) published the most documents in this field, respectively. The University of Birmingham was the most productive institution (n=1,441, 1.54 %). Meier, K. J. S was the most productive author (n= 119, 0.12%). Keywords with the highest frequency were "management", "governance", "government", "policy", "performance", "politics", "state", and "organizations". The most co-occurrence keywords existed within three clusters, the first including keywords related to policy issues, the second including author keywords about management and performance, and the third including keywords related to state and local management. The global trend of publications in the field of Public Administration has been upward, from 54 documents in 1923 to 4561 documents in 2020. This study not only presents a full view of global Public Administration research but also can contribute to future research in this field and bibliometric studies.

Bibliometric analysis of different fields of knowledge leads to a better understanding of the trend and quality of scientific products. The present study examined the publications on Altmetrics through bibliometric analysis and knowledge mapping. In this survey research, using quantitative indicators of scientometric, scientific developments in the field of altmetrics have been evaluated. The study population included all articles in the field of altmetrics (1077 documents) indexed in the Scopus database from the beginning to the end of 2020. The Excel and VOSviewer software packages were used to analyze the data. The findings show that scientific products in the field of altmetrics indexed in Scopus have been published since 2012; the quantitative trend of publications has been upward; Most of the scientific products in the field of altmetrics were original articles and in English. The United States, the United Kingdom, and Spain were the top and most productive countries in publishing documents in the field. Iran was ranked ninth with 52 documents. Regarding the number of publications, the University of Wolverhampton, the Administrative Headquarters of the Max Planck Society, and Leiden University were ranked first to third, respectively. Thelwall, M., with 42 articles, Bornmann, L., with 32 articles, and Haunschild, R., with 25 articles, were the most active authors. The most frequently used keywords were "Altmetrics", "bibliometrics" and "Social media". The highest number of documents in the field of Altmetrics has been published in the journal "Scientometrics". The most cited author was Thelwall, M., with 2691 citations. Due to the upward trend of scientific publications in Altmetrics and the beginning of its way, this upward trend will continue. Also, most of the top authors in the field are from universities and countries active in this field.

The advent of new technologies such as Machine Learning has highly influenced the health sector's activities; with this, there is an ease in diagnosis and decision-making processes in the sector. Hence, this study aims to analyze the application of Machine Learning in Smart Health research. This study uses 192 records from the Scopus database based on a well-crafted search term to identify nations with the highest publication output, the principal research subject areas, the top funding sponsors, and research keywords in this subject matter. The result shows that the first document on machine learning in smart health was published in 2011. The research output on this subject has dramatically increased, with India now being the top nation where research in this area is conducted. It was also discovered that the journal IEEE Access has the highest number of publications in this area. This analysis will help researchers, policy developers, and professionals in the health sector to better understand the development of Machine Learning in Smart Health research. Machine Learning in Smart Health portends Growth in the future.

Editorial board members (EBMs) of journals play a pivotal role in authentic international scientific journals. Editorial Board Interlocking (EBI) phenomenon reflects the effectiveness and importance of the scholarly journal's editorial boards in various scientific fields. The primary purpose of this paper is to conduct a Social Network Analysis (SNA) of EBI phenomena from the perspective of astronomy and astrophysics journals. The present study is applied research based on EBI, SNA, and the descriptive-analytical approach. The statistical population of this study consists of the editorial board members of all journals of astronomy and astrophysics indexed in the JCR and official journal websites. There are 1597 job positions in 67 astronomy and astrophysics journals occupied by the 1394 scholars. Data analysis shows EBI for 95 scholars and 79 organizations. "Aleksei A. Starobinsky" from Russia and the Russian Academy of Sciences, "Daniel J. Scheeres" from the United States, and the University of Colorado Boulder have the highest EBI contributions in five journals. "Daniel J. Scheeres," with a centrality of 39, has the highest degree of centrality measurement among the EBMs. The presence of more than five times as many men as women indicates that astronomy and astrophysics journals are considered "masculine" by the editorial board. The EBI phenomenon is observed in astronomy and astrophysics journals due to the limited number of peop le eligible for the editorial board. Due to EBI, a limited number of famous scholars are made macro-policies such as publishing the articles, referees selections, and the reviewing process. Astronomy and astrophysics journals have "elite" academic networks. Gender inequality exists among EBMs, and the majority of them are male. Accordingly, these journals are "men's journals."

The following article proposes a novel context by Information Quanta in the structural analysis of ontologies, which could be used to develop ontology evaluation metrics and measures. The identification of information quantum needs to clarify knowledge quanta in knowledge systems and semantic networks by considering two influential theories as Quantum Theory of Knowledge (QTK) proposed by Burgin (1995a; 1997; 2004) and the Semantic Link Theory of Knowledge (SLTK) proposed by Zhuge (2004; 2010; 2012). QTK identifies the quantum level of knowledge as knowledge quanta comprising the minimal blocks or units of knowledge in the construction of knowledge systems. In this case, knowledge quanta are primitive propositions and predicates. Elementary units of semantic networks, the triad of two nodes and a labeled semantic link between them, in SLTK based on the Semantic Link Network Theory (SLNT) could be conceptualized as knowledge quanta. Quantum units of knowledge are shared representations in the QTK and the SLTK. As a kind of semantic network, ontology also includes the triads of nodes and semantic links defined as knowledge quanta here. A semantic link as a knowledge quantum can be divided into its components, i.e., into three parts: subject, object, and relation. These separate parts can be considered as the information quantum or semantic network data. Finally, it can be said that the information quantum or data in the semantic network of ontologies that include the subject, object, and relation are derived from the fragmentation of the semantic links into their components. Identifying information quanta in ontologies could play an influential role in establishing and developing a new context in the structural analysis of ontologies through proposing, developing and applying new metrics and criteria in measurement of the mentioned quantum elements (i.e., ontology data).

This paper provides a comparative analysis of cross-lingual word embedding by studying the impact of different variables on the quality of the embedding models within the distributional semantics framework. Distributional semantics is a method for the semantic representation of words, phrases, sentences, and documents. This method aims at capturing as much information as possible from the contextual information in a vector space. The early study in this domain focused on monolingual word embedding. Further progress used cross-lingual data to capture the contextual semantic information across different languages. The main contribution of this research is to make a comparative study to find out the superior impact of the learning methods, supervised and unsupervised in training and post-training approaches in different embedding algorithms, to capture semantic properties of the words in cross-lingual embedding models to be applicable in tasks that deal with multi-languages, such as question retrieval. To this end, we study the cross-lingual embedding models created by BilBOWA, VecMap, and MUSE embedding algorithms along with the variables that impact the embedding models' quality, namely the size of the training data and the window size of the local context. In our study, we use the unsupervised monolingual Word2Vec embedding model as the baseline and evaluate the quality of embeddings on three data sets: Google analogy, mono- and cross-lingual words similar lists. We further investigated the impact of the embedding models in the question retrieval task.

Intellectual property laws should not be strict protection frameworks for free Access to Information. Instead, as digital space has made it easier to access Information and blur the geographical boundaries of knowledge, Access to Information is permitted for all by amending intellectual property laws nationally and internationally. This is a quantitative study to bridge the gap between the richness and poverty of Information and a means of disseminating knowledge. The Information needed to answer the questions of this research was collected using a researcher-made questionnaire (content analysis and Delphi panel) consisting of five main components (publisher, author, publications, subject, and commercialization) and 63 questions. Questionnaires were sent to the study's statistical population, which was all the open-access medical journals approved by the Ministry of Health. Based on the type of variables, data were described with mean and standard deviation indices for quantitative and frequency variables and frequency percentages for qualitative variables. The collected data were analyzed using SPSS software version 24. The findings of this study are presented in several different tables to examine the intellectual property components and the databases indexing medical journals. Publications indexed on all three sites of Scopus, Web of Science, and PubMed are components one and three due to deviations from the norm. The Kruskal-Wallis test was used to examine the uniformity of the score distribution of the components mentioned in the indexes. Only the four components of normality are established. According to the findings, all components have a significant relationship with the index, language, publisher, and time of publications of the Ministry of Health. This questionnaire can be used to provide an intellectual property model for open-access medical journals. And using the presented model to review and evaluate open-access journals in the field of medicine.

This study evaluated the scientometrics indices of Iranian medical sciences journals indexed in Web of Science, Scopus and PubMed databases until 2020. The present study is a descriptive and practical survey which was done using scientometric methods. The source of data collection includes Web of Science, Scopus and PubMed databases. Excel statistical software was used to analyze the data, and net draw software was used to plot the graphs. A survey on Iranian medical journals' status revealed that the number of journals in all three databases has been growing. "General and Internal Medicine", "Health", and "Pharmacology, Toxicology and Pharmacy" are the subjects with the highest number of indexed journals in these databases. Furthermore, a qualitative review of indexed journals showed that more than 70% of Iranian journals have an impact factor of less than two. "International Journal of Health Policy and Management" of Kerman medical sciences university and "Bioimpacts" of Tabriz medical sciences university are the only medical journals with impact factors greater than 3 (5.007 and 3.831).

Generally, despite the significant growth of indexed medical journals in recent years, most Iranian journals are not ranked among high-quality journals according to global indexing criteria.

The study evaluates ICT facilities and their use by Kenyatta University Postmodern Library patrons. The study's objectives were to assess the available ICT facilities in Kenyatta University Post Modern Library and determine the purpose of using the facility and the challenges patrons face while using ICT facilities. The study employed descriptive survey research; 120 respondents were chosen as the population. Total enumeration was used as the sample size. A convenience sample technique was used for the study. The study used a questionnaire as a major data collection instrument; it was administered to 120 Kenyatta University Post Modern Library staff patrons through the Google form platform. Data collected were analyzed using descriptive analysis through frequency and percentages. The study revealed that computers, printers, the internet, and photocopying machines, among others, are the available ICT facilities in the Library. The finding also indicates that the available facilities are used for scanning, photocopying, surfing the internet, and researching. The study recommends that the Library should improve internet connectivity by increasing bandwidth. The Library should improve on training the users on ICT skills to enhance the use of ICT facilities in the Library; the Library should seek funds to enable it to acquire more ICT facilities.

This paper analyzed the literature on collection development, space planning, futuristic technologies, and information services related to academic libraries. The content analysis method was applied to review these papers. The selected papers for review have the potential to influence the future of academic libraries. This review of the related studies shows that the academic library has evolved into a hybrid model, combining traditional collections and a modern, sophisticated knowledge warehouse. It is predicted that the future library will be a place for aesthetic, emotion-rich social centers and will act as a knowledge refinery. Developing innovative technologies and services and improving the skills of library staff are significant challenges for the future. This study has designed a new conceptual framework in this area, identifying the possible scenarios for future academic libraries.

Despite Emails and websites being widely used for communication, collaboration, and day-to-day activity, not all online users have the same knowledge and skills when determining the credibility of visited websites and email content. As a result, phishing, an identity theft cyber-attack that targets humans rather than computers, was born to harvest internet users' confidential information by taking advantage of human behavior and hurting an organization's continuity, reputation, and credibility. Because the success of phishing attacks depends on human behavior, using the Health-Belief Model, the study's objective is to examine significant factors that influence online users' security behavior in the context of Email and website-based phishing attacks. The model included eight predictor variables and was validated using quantitative data from 138 academic staff. The study findings exhibit that 4 out of 8 predictor variables, namely Perceived-Barriers, Perceived-Susceptibility, Self-efficacy, and Security-Awareness, are statistically significant in determining users' security behavior. The study's outcome is to assist in the appropriate design of both online and offline content for cyber security awareness programs, focusing on Email and website-based phishing attacks.

The main function of a library is the availability of information resources. To achieve this goal, it is necessary to correctly store and retrieve documents and information in libraries and information centers. This study mainly aimed to design a model of challenges and opportunities for storing and retrieving information in Iran public libraries from the librarians' perspectives. The practical research approach is based on the grounded theory in terms of the purpose. Using the grounded theory qualitatively, sampling was conducted by targeted (judgmental) and snowball (chain) techniques for the theoretical saturation of data. Interviews were done with 26 senior public library experts with experience and expertise in this field. Results of the analysis of the data obtained from the interviews show that management, policy-making, and fiscal mechanisms were the primary underlying conditions. Individual and organizational factors were influential under intermediate (intervening) conditions. The approaches of the model of challenges and opportunities for storing and retrieving information include creating an environment for the employees' growth and development and modifying the organizational structure in public libraries of Iran. The presently designed model consists of adequate dimensions and components, casual, underlying, and mediating conditions, and constituting elements, which show the central phenomenon, consequences, and strategies for implementing public policy. Finally, practical suggestions were presented for improving the storage and retrieval of information in the Iranian public libraries.

Health information-seeking behavior is how to search, find and use disease-related information, information about health-threatening factors and activities related to health promotion. One of the issues affecting people's quality of life is chronic diseases, of which cancer can be mentioned. Cancer incidence is rising over the last years . It cannot be stated for sure that the Fear and concern about cancer which is named carcinophobia,  always cause a lack of follow-up and avoidance of people seeking cancer information; however, considering different time intervals and in different cultures, the same Fear and concern as the stimulus, stimulates or forces the people to track and seek cancer information.The purpose of this analytical survey was clarifying the situation of Health information-seeking behaviour among university students both undergraduate and postgraduate as academic population during cancer outbreak. Also our aim is to  determine the relationship between carcinophobia and information-seeking behavior in this population. Research findings while clarifying the situation of Health information seeking behavior in the academic population, can indicate that carcionphobia causes more information search or is a barrier to information search. The samples of this analytical survey include 243  college students who were selected by cluster-class methodology. The research tool was derived from the Cancer Information Questionnaire Levin (L_CIS). Pearson correlation test was used for the relationship between variables. The results showed that the average total score of students' fears of the disease was 27.20, which was high and the main motive for the search for cancer health information was the protection of personal hygiene(56.4%). " Knowing how to treat cancer (54.7%) and the awareness of new trends in medicine (44.5%) were in the second and third rankings of the purpose and motivation of the search for information. Three components including "Lack of effective communication with Treatment staff  (such as physicians or nurses), "Lack of mastery in searching or finding of health information resources" and "Lack of mastery in the use of print or online health information resources" in average were the most important problems and barriers to obtaining the required information resulting from Fear of cancer. With increasing Fear of cancer, people's willingness to search for information through friends and watching TV shows increased, but the severe, and morbid Fear of cancer reduced the desire of individuals to seek health information.

In addition to being utilized in areas such as Information Storage and Retrieval and Knowledge Management, investigating human information behavior as an independent field of knowledge has its issues. The concept of info-behavior somehow involves a reciprocal process: the info-giver and the info-receiver/seeker. On the other hand, in a logical analysis of information behavior, the elements required in this process are information and the source of information (i.e., the info-giver). Nevertheless, most of the discussions and the papers found in the literature on human information behavior (perhaps because of being interested in the applications mentioned above) are focused on info-seeking. And for any reason, little attention is paid to the role of the info-giver as the primary side in information behavior. However, the author's main idea in this paper is that the info-giver is central to realizing this process. The present article, having a glance at some of the most popular models on information behavior and the place of the info-seeker in the process, points to the absence of the info-giver in the mentioned models. Then, by providing some exemplary cases of information behavior initiated by the info-seeker/receiver in the absence, the paper emphasizes the information giver's central role in realizing the information behavior process.

This paper aims to investigate how a Persian spoken poetry game, called Mosha'ere, can be computerized by using a Persian automatic speech recognition system trained with read speech. To do this, the text and recitation speech of the poetries of the great poets, Hafez and Sa'di, were gathered. A spoken poetry rhyming game called Chakame, was developed. It utilizes a context-dependent tri-phone HMM acoustic modeling trained by Persian read speech with normal speed to recognize beyts, i.e., lines of verses, spoken by a human user. Chakame was evaluated against two kinds of recitation speech: 100 beyts recited formally at the normal rate and another 100 beyts recited emotionally hyperarticulated at a slow rate. About 23% difference in WER shows the impact of the intrinsic features of emotional recitation speech of verses on recognition rate. However, an overall beyt recognition rate of 98.5% was obtained for Chekame.

The present study was conducted to provide a suitable model for book distribution in Iran. This research is applied in terms of purpose, and the research method is mixed (qualitative: grounded theory; and quantitative: analytical survey). The data were collected through a series of semi-structured interviews at the qualitative stage. The population of the qualitative section consisted of 10 book distribution experts who were selected by using the snowball method; for the second population, 118 book distributors were purposefully selected, and the research questionnaire was distributed among them. The MAXQDA software was used to determine the qualitative section's concepts, categories, and subcategories. Then the paradigm of book distribution in Iran was identified. The model was determined using PLS software in the form of descriptive statistics and structural equation modeling in the quantitative section. In the qualitative section, the five cultural, economic, legal and political, substructural, and professional factors were identified; the results of the quantitative section showed that the cultural dimension had a weak relationship with distribution factors, and the relationship was vital for other dimensions. It can be said that the cultural dimension has the lowest intensity of the relationship, and the substructural dimension, economic dimension, professional dimension, and legal and political dimension have the highest intensity correlation with distribution factors, respectively. The most influential factors influencing book distribution were the lack of reading culture, inadequate distribution, unprofitability, weak rules, and unprincipled publishing support. The most effective way to improve the distribution was to strengthen the professional distributors. Distribution channels of goods and cultural services in Iran are mainly traditional. Moreover, the traditional distribution network, lack of use of new technologies, the long flow path of goods, the minimal share of bookstores in the distribution system, weakness of distribution substructures, lack of manpower skills in the distribution sector, and lack of capable public and private distribution networks cause inefficiency of the book distribution network and result in consumer dissatisfaction.

Social media, widely known by the public, has become one of the tools to facilitate written expressions in daily life. The adoption individuals from various backgrounds use this technology, ranging from children, adolescents, adults, and the elderly. Social media positively influences human life, but various parties can also misuse it with harmful desires. One example of adverse treatment on social media is cyberbullying, which is now no longer a stranger in social life. In this research, the Social Network Analysis method is chosen to identify the distribution patterns of cyberbullying on social media. This method is used to analyze the required metrics such as indegree centrality, outdegree centrality, betweenness centrality, and reciprocity to understand the reasons for the spread of an event. This study has understood the distribution patterns of cyberbullying actions on social media by looking at communication between users and their relationships to find out the reasons for the perpetrators of cyberbullying actions. This result significantly impacts the community by better understanding the procedures in social media to avoid other users' bad behavior.

Since scientometrics has changed significantly over time, study of its changes can include a description of the past, an analysis of the current situation, and planning for the Future, leading to optimal policymaking and planning by organizations. The objective of the present study was to identify trends and driving forces affecting future research in the field of scientometrics in Iran based on the characteristics of the knowledge-based society. This study is applied that has conducted by literature review and survey. An expert panel was conducted with 15 experts in the field of Knowledge Science. Then, a researcher-made questionnaire was distributed among the experts. The study results showed that the driving forces affecting the Future of scientometrics can be divided into 14 general indicators (10 internal indicators including communication and interactions, experts, creativity and innovation, information technology, citation, methodology, index, language barriers, facilities, and specific problems of the field and 4 external indicators including sociology, economics, information technology and policymaking and management of the country's higher education system) with 66 items. Given the undesired situation of trends of scientometrics in Iran, policymakers and managers of the country's higher education system in Iran should consider the need to change the trends and the effective drivers of scientometrics because the lack of synchronization with the changes, the effectiveness, and applicability of research will reduce and faded over time.