International Journal of Information Science and Management
Volume:20 Issue: 4, Autumn 2022

Natural languages usually contain context, which is difficult for a machine to understand. Sentiment analysis is a contextual mining technique often used in NLP to identify, understand and extract subjective information in texts, such as people’s comments, feedback, reviews, and opinions. Sentiment analysis is a useful tool for finding the polarity of a sentence. Sarcasm detection is one of the complex areas of sentiment analysis. Sarcasm flips the polarity of the sentence identified by sentiment analysis. Thus, sentiment analysis results may get biased if people use sarcasm in their text. Hence, to understand the sentence's real meaning, we proposed a system of sarcasm detection on tweets using an ensemble approach. We performed sarcasm detection with and without #sarcasm. After training a model and observing earlier studies, We found that the presence of #sarcasm gives a better result. Therefore the author tried implementing a model where #sarcasm is removed from the tweets, and the model is trained. After comparing both models' presence and absence of hashtags, it is found that the lack of the hashtag model works well, which can be used on any plain text without any clue of sarcasm.

According to the administration of research data and funding for governmental organizations and funding agencies, the National Research Council of Thailand (NRCT) employs a National Research Management System (NRMS). NRCT needs different categories of data to provide information to various government departments to make policy decisions related to research funding. NRMS has so far collected a significant amount of such data. However, the tools needed for prompt analysis of such large amounts of data are inadequate. The purpose of this article is to discuss a multi-dimensional report system to provide enhanced information to support the decisions of policymakers. This involves creating reports with diverse views based on the numerous fields in the system, such as sorting by year, funding entity, ministry, department, policy and research strategy, and research issues, etc. and exhibiting a dashboard report to the officers and executives responsible for decision-making in the form of an overview of national research data by using Business Intelligence (BI). For the development of the report system, the research uses Tableau software. The officers who assessed the proposed report system expressed satisfaction, as shown by the outcomes of the user evaluations. A key feature mentioned was the ability to submit more reports to high-level administrators quicker.

The utility of scientometric considerations helps in dynamic/approach making. Technology forecasting provides an informed view of technology, its development, and future trends and is an essential tool in decision-making. BRICS is the abbreviation authored for a relationship of five significant arising public economies such as Brazil, Russia, India, China, and South Africa. The BRICS nations are now fortifying collaboration to battle environmental change through a progression of joint goals. The BRICS should deliver these by consenting to make and advance the strides logically known to do the most to control environmental changes. Scientometrics is progressively being applied in science strategy examines. The present study attempted to find the year-wise, language, document type, and keyword-wise distribution of articles in Climate Change research and to study the authorship pattern and collaboration in climate change research. It attempted to present the exponential growth rate of Climate change and top-cited documents in Climate change research. Using the search term “Climate Change” the data were retrieved from the Web of Science from 1994 to 2018. Totally, 30,270 records were downloaded and analyzed by using Bibexcel. The collected data have been analyzed with the Bibexcel and VOS viewer and presented in the form of tables and pictures. The study found that more number of articles published in the year 2018 was 5756, and most documents were published in English; multiple authors contributed 96% of the articles. It is understood that PLOS One published 581 documents, lesser level of exponential growth rate noticed in 2009 was 0.7. The significance of the support of Brazil and BRICS in a global environmental change system has been perceived for quite a while. The present research exploration discussed the distributions of BRICS, which have taken for following climate change publications. They feature that worldwide climate change activity can't be effective without BRICS nations' contribution.

The present study was conducted with a scientometric approach and using the social network analysis method to investigate the relationships in the field of intangible assets. In this regard, the data of 2998 documents conducted between 1979 and 2019 based on the articles indexed in the Scopus database on intangible assets were analyzed using Gephi and Publish or Perish software. The status of scientific productions in this field and the most influential concepts and keywords, researchers, and journals were examined. Research findings show that knowledge management and intellectual capital are essential concepts in this field. Also, value creation, value chain, social responsibility, and trademark are the most valuable subject areas based on the networks. The co-authorship network is discrete, with low density and 58945 citations in all articles. Also, Emerald Publications has published the most significant number of articles in this field. Entering the era of a knowledge-based economy, a large part of organizations' assets is intangible, which confirms the identification and investment in these types of assets. This study shows that intangible assets are closely related to critical social issues such as intellectual capital, knowledge management, and competition. The present study helps researchers in this field explain the investigation process and policies based on the identified areas of influence.

Communication is the most fundamental process in research; therefore, scientific communication is the main center of the growth and development of the scientific community. Scientific communication means how scientists in each discipline can disseminate their information and knowledge through formal and informal channels. This is usually done through various media such as books, articles, conference papers, etc. This research has been conducted to investigate the scientific collaborations of Dr. Mehrad, “as an impressive specialist” of knowledge and information science in Iran, using the bibliometric method. The findings showed that about 180 works (including 57 books, 52 Persian articles, 22 English articles, 11 research projects and 38 dissertations) had been published by him. The study of Dr. Mehrad's scientific collaborations showed that 27.8% of the works were published as single authors and 72.2% as the group works. Dr. Dayani is at the top of his scientific colleagues with the publication of 9 works. The journals "Library and Information Science", "Social Sciences and Humanities of Shiraz University", "Information Processing and Management," and" Journal of Academic librarianship and information research" were the four journals in which most of Dr. Mehrad's works were published. The fields of "Library and Information Science", "Databases", "Shiraz University", and "Evaluation" are the core topics in which most of his works have been published.

Other languages have influenced Arabic because of several factors, such as geographical nearness, trade communication, past Islamic conquests, science and technology, new devices, brand names, models, and fashion. As a result of these factors, foreign words are used in Arabic text and are known as Arabised words. Arabised words affect the Arabic natural language processing (NLP) task because identifying a correct stem or root from an Arabic word becomes more difficult. Therefore, a more efficient Arabic NLP can be developed if Arabised word removal is part of a pre-processing task. In this paper, we propose an algorithm for detecting and extracting Arabised words as a pre-processing task for an Arabic stemming task. This algorithm is a combination of lexicon-based and rule-based approaches. The lexicon list has been developed based on various sources of Arabic text resources, and the rule-based algorithm has been designed to cater to Arabised words with definite articles and use pattern matching on prefixes and suffixes. To evaluate the effectiveness of the proposed Arabised word removal algorithm on the Arabic NLP task, we use Arabised word removal as part of pre-processing in Arabic stemmers. Three Arabic stemmers are used in our evaluation, namely, light stemming, condition light and ARLS, on three types of Arabic standard datasets. Comparisons were made by measuring the performance of precision, recall and IFC on the stemmers with or without our Arabised word removal pre-processing. Results show that the performance on all the stemmers improves if Arabised word removal is included as part of the stemming's pre-processing. Therefore, an efficient Arabic NLP application or task can be developed if Arabised word removal is included in the pre-processing stage for Arabic NLP application, mainly Arabic stemming.

Policymakers and experts should trust health studies. On the other hand, it should be considered by the general public. Altmetrics, as a new method, seeks to examine the social effects of researchers' scientific outputs along with citation analysis indices. The present study aims to investigate the effectiveness of the articles published by researchers in the field of waterpipe/cigarette smoking on the Web of Science database during 2010-2019. This paper is a descriptive-analytical study with a correlational approach in the citation analyses using the Altmetrics index. The statistical population consists of papers on waterpipe/cigarette smoking by Middle Eastern researchers during 2010-2019 published on the Web of Science. The data is extracted using the Altmetrics Bookmarklet and analyzed it by excel and SPSS.From the total number of scientific articles in the field of waterpipe/cigarette smoking by Middle Eastern researchers during the research period, 1,086 articles were indexed on the Web of Science, and only 2% of them had no Digital Object Identifiers (DOI) or PubMed Identifiers (PMID); on the contrary, 50% of the articles had Altmetrics scores. Among the social networks cited by the researchers of the Middle Eastern countries in the field of waterpipe/cigarette smoking, the shares of social networks, namely Dimensions, Mendeley, and Twitter, were the most. The most significant number of citations of the articles on Mendeley and Twitter belonged to U.S. and U.K. users. Also, medicine and dentistry had the highest number of Mendeley citations. The correlation coefficient between the altmetrics score and citation index was poor but significant (R=0.32, P <0.05). The publication of research papers on the social web (i.e., social networks) increases the visibility of the documents and makes them visible to a broad audience. This is effective in the future of citations of articles on citation databases. This further increases the qualitative performance indices of the papers by receiving more citations.

The study focuses on Research Data Management (RDM), aiming to demonstrate how RDM is evolving globally. It provides a systematic mapping of the current literature to aid in identifying core coverage and reflecting on potential trends using the scientometric technique. For detailed thematic analysis, performance analysis, network representation, science mapping, and scientific collaboration, this study used bibliometric tools such as the R package Biblioshiny, ScientoPy, and VOSviewer. Two premier indexing databases, SCOPUS and Web of Science, which extensively cover RDM literature, are appropriately considered. Furthermore, all retrieved documents are refined by language, document type, and irrelevant keywords for practical analysis. This study covers the Research Data Management (RDM) literature from 1926 to 2020, with 6263 documents published from 1666 sources and 15,545 authors. The most common domains discovered in RDM research are Computer Science, Library and Information Science. RDM is primarily familiar and cultivated in nations such as the United States, China, the United Kingdom, Canada, Germany, and Australia are pioneers in RDM research. The findings are vital for researchers working on RDM projects and policy formulation. This research helps to identify the literature's strengths and potential gaps. This secondary data contributes significantly to the scientific landscape in scientific production, network architecture, source clustering, and international collaboration, the evolution of dominant subjects and countries, and science mapping of productive word frequency.

Mental health problems have become one of the global health burdens, according to the reports from World Health Organization in 2020. By realizing the potential increase in mental health problems worldwide, the encouragement of help-seeking behaviour is pivotal to tackling the issue of mental health. Thus, this study aims to present the bibliometric analysis of help-seeking behaviour for mental health problems focusing on employees by using the Scopus database. The specific keywords and terms that fulfill the criteria related to this study were executed. In general, this study found that the research trends in help-seeking behaviour are growing but still lack empirical evidence that can help fully understand the scenario in the work context. Hence, further studies are warranted to improve the apprehensions on the issue.

The current study aims to calculate the relationship between Altmetric scores obtained from the observation and dissemination of digital library resources in the Dimensions database and the number of citations received in the Scopus database. Also, in another part of the research, the predictive power of the number of Scopus citations by Altmetric scores is examined. The present research is applied in terms of purpose and survey-descriptive in terms of type, which is done by the scientometric method and with an Altmetric approach. The statistical population of the study includes all articles in the field of digital libraries (24183 records) that are indexed in the Scopus citation database during 1960-2020. Dimensions database has been used to evaluate the Altmetric scores obtained from these articles on social networks. Due to the limited access to the required data in the Scopus database, 2000 highly cited articles in the field of digital libraries in this Scopus database were studied through the Dimensions database. The data collection tools are Scopus Citation Database and Dimensions Database. The required data is collected through the Scopus database. In this study, the studied indicators from the Dimensions database appear as the independent variable of the research. The dependent variables in this study are the number of citations to articles in the Scopus database. Correlation tests and multiple regression between the studied indices are used to examine the relationships between variables and perform statistical tests. The software used is Excel and SPSS version 23. The present study results show that the social networks Patent, Facebook, Wikipedia, and Twitter have the highest correlation with the number of citations in the Dimensions database. The social networks Blog, Google User, and Q&A do not significantly relate to the number of citations received in Dimensions. Patent social networks, Wikipedia, and Twitter have the highest correlation with the number of Scopus citations. In this case, the social networks of Blog, Google User, Pulse Source and Q&A do not significantly correlate with the number of citations received. Among the citation databases studied, Mendeley has the highest correlation between the numbers of citations. Other results indicate that the publication and viewing of documents on social networks cannot predict the number of citations in the Dimensions and Scopus databases.

This paper aims to synthesize findings drawn from studies on knowledge leadership to identify the key trend of research in the knowledge management literature over the past two decades. A systematic literature review was performed over a data set of 149 related studies published in the international journals indexed by the WoS, SCOPUS, ProQuest, Google Scholar, Emerald Insight, and Elsevier databases between 2001 and 2021. The findings conceptualized the nature of “knowledge leadership” and revealed six core themes focusing on multiple leadership styles, knowledge leadership for learning, effective KM leadership, leader-member exchange, and customer knowledge leadership. Additionally, the content analysis revealed the importance of knowledge leaders being more transformational, distributed, empowering, and visionary. It has been widely reported that transformational leadership is a significant driver of knowledge management practices in the organization. This study provides an integrated picture of effective knowledge leadership for managers and practitioners that significantly depends on a paradigm shift from hierarchical structures and traditional models of leadership to the use of shared, distributed, and networking leadership. Given this increasing interest in studying the role of leadership in KM, it is interesting to investigate the research trend of knowledge leadership in the KM literature.

Cloud computing has become one of the newest and most popular topics in the field of the Internet. Pricing is one of the main factors that can affect the successful implementation of cloud computing. Due to the large volume of research conducted in this field, the purpose of this study is to review the cloud computing pricing literature using a Computational Literature Review (CLR) and identify influential trends in this field. For this purpose, the publication and citation trends are first identified. The most influential authors, journals, and articles are then determined using citation analysis. Next, the structure of the co-occurrence network of keywords is analyzed using three centrality measures degree, betweenness, and closeness. Finally, the thematic trends are identified using a positional analysis based on centrality measures. According to the obtained results, research in this field has grown significantly. Keywords such as edge, computer architecture, and distributed computing have recently come to the fore. Also, words such as model, energy, allocation, strategy, auction, design, and reliability have been among the most influential in this field. The positional analysis indicates that the researchers are trying to overcome resource scarcity through three lines of work: resource provision, resource allocation, and resource distribution. Trends show that the cloud industry is highly attractive and will also have high growth. In the future, we will also see an increase in the use of value-based pricing methods in cloud computing and research in this area.

The digital library has gained significant importance in recent years as it provides a more suitable solution to access the knowledge or resources available anywhere and at any time. National Digital Library of India (NDLI) is a digital platform that provides access to substantial digital storage of resources and encourages and inspires learning among the nation's people. This study aimed to analyze the awareness of the National Digital Library of India (NDLI) among the students, teachers and research scholars of India and tried to assess its utilization and backdrops for further improvement. The empirical study was conducted in India, and the primary data were collected using Google Forms. Snowball sampling was used to collect data from 384 respondents, including students, research scholars and teachers. The study detected that the overall level of awareness of NDLI was low (39.3%) among the different groups, and students had the lowest (50.2%) level of awareness among other groups of respondents comparatively. A strong association was seen to exist between educational qualification and respondents’ level of awareness. Apart from these, the users found the NDLI app useful; 54% of respondents were able to access the required content using the app and 71% of the users rated ‘good’ the app's performance.

Currently, most linguistic studies benefit from valid linguistic data available at corpora. Compiling corpora is a common practice in linguistic research. The present study introduces two specialized corpora in Persian; a specialized corpus is used to study a particular type of language or language variety. For building such corpora, first, a set of texts were compiled based on pre-established criteria used in the sampling process (including the mode of the texts, type of the texts, domain of the texts, language/ language varieties of the texts and the date of the texts). The corpora are specialized because they include technical terms in information processing and management, librarianship, linguistics, computational linguistics, thesaurus building, managing, policy-making, natural language processing, information technology, information retrieval, ontology and other related interdisciplinary domains. After compiling data and Metadata, the texts were preprocessed (normalized and tokenized) and annotated (automated POS tagging); finally, the tags were manually checked. Each corpus includes more than four million words. Since not many specialized corpora are built in Persian, such corpora could be considered valuable resources for researchers interested in studying linguistic variations in Persian interdisciplinary texts.

The new media and technologies in the information era have affected all aspects of individuals in the information society. This research aimed to investigate the motivations for using Instagram as a social network among students of the Psychology and Educational Science Faculty of Semnan University. The present study was a survey in terms of methodology and applied research in terms of purpose. The research population comprised 442 students in the Faculty of Psychology and Educational Sciences at Semnan University. Totally, 205 individuals were selected through simple random sampling. Based on Gülnar, Balci and Çakir questionnaire (2010), a measure was provided for data gathering. To assess students' motives in using Instagram as a social network, exploratory factor analysis, one-sample t-test, and description analysis were used, and the collected data were analyzed using SPSS software (version 24). Findings showed that six factors of narcissism and self-expression, passing the time and entertainment, curiosity about events and memories, information seeking, creating social and emotional capital, and relationship maintenance were the most important motivations for students to use Instagram as a social network. The results further showed that three factors (i.e. information seeking, passing time, and relationship maintenance) were suggested as the three main motivations of students. Psychology students of Semnan University use social networks such as Instagram according to real-life conditions to compensate for their shortcomings and deficiencies and meet their needs.

Illiteracy can be a significant obstacle to any given country's economic and social development. Hence, exploiting the potential of Information and Communication Technology (ICT) can help solve this problem by creating proper solutions for the illiterate and low-literate population. This study provides search and retrieval strategies for Iran's illiterate or low-literate population by designing an appropriate website. The research method in this study is mixed. A total of 65 individuals were selected using the snowball sampling method. First, by designing qualitative research of ethnographic type, we examined the critical information needs of the research sample. After equalizing the process and information needs, a website was created for the research sample and was provided to them. The designed website does not require human assistance to search for information. In addition, the website uses graphic and audio content related to local culture and language. ISO-9241-11 standard was used to evaluate the performance of the website designed in the research. Furthermore, it examines the characteristics of participants, i.e., gender, and previous experience of using computers and mobile phones on the website's usability. Since the present study population was low-illiterate and illiterate, the research time to prepare them to answer the questions was very long. The results revealed considerable effectiveness, efficiency and satisfaction with the website among the participants. Moreover, the gender variable did not affect how they use the website and their inclination in this respect. Providing the services required by this group of users in any way, including appropriate cyberspace, increasing literacy rates and meeting the information needs of this group at a far lower cost than traditional education, can be taken into account as one of the requirements of governments. The current study is the first experimental research to measure the needs and create suitable tools for using the virtual world on the part of low-literate and illiterate people in Iran.

As an active and emerging research field, knowledge strategy receives extensive academic attention and acts as a compass for knowledge management strategy. The main purpose of our research is to discover and visualize emergent and transient grouping of concepts and underlying research issues and their citation and co-citation footprints in knowledge strategy scientific literature. Based on the publications from Web of Science core databases from 1965 to 2018, a total of 403 publications matched the search criteria of this study. CiteSpace is applied for visualizing and analyzing trends and patterns of knowledge strategy scientific literature. Google Fusion application is used to show data distribution of knowledge strategy. This study showed that the area distribution of knowledge strategy research is worldwide and has spread especially in the United States, Europe, and other countries. According to this study, knowledge strategy and management are the research front keywords with more citations. Zack (1999) and Alavi (2001) are knowledge strategy's most prominent intellectual bases. Identifying emerging trends and abrupt changes in knowledge strategy are among the results of this study.

Knowledge management has an increasing role in knowledge-based organizations. Academic libraries have become an essential part of knowledge organizations, and knowledge management is vital. Therefore, this study addresses the challenges of knowledge management processes in Islamic Azad University libraries. This is applied research using the survey-analytical method. The study's statistical population included 60 managers of central libraries at Islamic Azad University. Due to the limited managerial staff, we employed the complete enumeration method. Data were analyzed using SPSS software. The study of eight factors showed that knowledge characteristics, knowledge source, communication channels, time, management, and technological factors had lower scores than the population average, which is a challenge for libraries. Both organizational and personal factors score higher than the population average, which is an opportunity for libraries. It seems that to improve the current situation, the managers of the libraries of the Islamic Azad University need to pay serious attention to the establishment of knowledge management and use the organizational ability and motivated workforce to meet the challenges and improve.

Scientific progress has been one of the critical concerns of many nations in recent decades. It has become one of the top priorities at the highest policy-making levels in several countries. During the last two decades, several policies have been developed to achieve scientific progress and leadership in different parts of the world. For example, China, Japan, Turkey, Saudi Arabia, and Iran have designed their policies to accelerate scientific progress and achieve scientific leadership in a specific region. However, there is no comprehensive framework to measure the extent of scientific leadership in theory or practice. This study proposes a multidimensional framework for measuring scientific leadership in countries through a qualitative approach. To address this objective, key dimensions, indicators, and metrics for measuring scientific leadership were identified in the literature and policy documents. After the identification of these dimensions, indicators, and metrics, they were verified and weighted by different expert panels. According to the findings, a comprehensive framework for measuring scientific leadership includes five dimensions and 22 indicators and metrics. Results showed that “institutions” is more important than other dimensions in the framework. Since the nature of “scientific leadership” concept is more political than scientific, considering dimensions and indicators covered by the media is a more effective way to measure it. The findings of this study can give policymakers a more comprehensive and accurate view of the concept of scientific leadership and assist them in various planning and research policies. In addition, the proposed framework is the basis for future research seeking to assess scientific leadership quantitatively.