Volume 75, Issue 1

This study was conducted to determine the factors influencing the adoption of green libraries for environmental sustainability, to find out the impacts and challenges faced by the librarians to adopt green libraries. For the systematic literature review, the study adopted the “Preferred Reporting Items for the Systematic Review and Meta-analysis” (PRISMA) as the methodology. Different search tools and techniques to access the relevant but extensive literature for the study were applied. Taylor and Francis, Emerald, Sage, IEEE, Elsevier, Wiley, EBSCO, Scopus, and Google Scholar were used to search the required literature. Initially, 844 documents were retrieved and after applying inclusion/exclusion criteria, finally, 33 papers were finalized to conduct the systemic literature review. The findings revealed that external, internal, and institutional goals, technological advancements, Green Library (GL) initiatives, and sustainable development goals (SDGs) are the major factors in adopting GL. Funding issues and the lack of technology are the major challenges faced by librarians. This study is beneficial for the administration, policymakers, LIS schools, and library professionals to gain awareness, planning, and execution to establish green libraries.

Media news around the world contains powerful signals for understanding governments’ thoughts and public reactions to domestic or foreign conflicts. Although the development of information technologies makes it possible to evaluate this big data in digital media and see perspectives on international issues, few studies have been conducted on news media. This article aims to investigate the dimensions in the British press surrounding the Ukraine War, which began on February 24, 2022. In this context, we examine 14,316 news articles covering the war in Ukraine from The Guardian , The Daily Mail , and The Times over the first 16 months using the LDA method, followed by advanced analyses. Through statistical analysis, the frequencies of the dimensions appearing in the news were compared and their intersections were examined. Additionally, thematic differences in the coverage of the Ukraine War were observed among British newspapers with different political tendencies. This study is one of the first to reveal the main dimensions of the war through newspaper coverage, aiming to understand the dimensions of the conflict affecting a country that is not directly involved in the war but aligned with one side.

This article reports the findings of a study of the educational backgrounds of library directors at Minority-Serving Institutions (MSIs) in the United States. Using a content analysis of MSI library websites and director/dean profiles, the leadership of 746 minority-serving institutions was identified including whether they have earned an American Library Association-accredited Master of Library and Information Science (MLIS) degree and from which library and information science (LIS) program it was earned. The study found that 83.8 % of MSI library directors held a MLIS degree though the percentage can vary dramatically based on MSI type, with only 50 % of Tribal College and University directors possessing this degree compared to 92.6 % of Historically Black College and University library directors. The LIS programs with the greatest number of MSI library director alumni are San Jose State University, the University of North Texas, and the University of Illinois, though the top programs for educating these MSI library directors also varies based on the MSI type. The findings of this study have implications for better understanding MSI libraries and the role of LIS programs in preparing future MSI library directors.

Although global scholarly communication should include regional diversity it has been centered on English-language journals published in Western countries that wield strong economic power. Intending to reduce epistemological disparity, this study examined the characteristics of OA diamond journals (OADJ) published in non-English speaking countries (NESC). This study analyzed the OA Diamond Journals Study Dataset which cOAlition S commissioned. From the dataset 1,496 journals from 84 countries were assessed in terms of the official language of the journal’s publication country, the regions of the publication country, the country’s GDP, and the journal’s language. More than 80 % of OADJ were published in NESC and European countries, with Latin America and high-income countries as the main regions. OADJ in Latin America tended to be registered in Latin American index systems and considered international readers less important. Among OADJ published in Africa, Asia, and Eastern Europe, and those published in English, the intention of moving away from OADJ was stronger and journal impact and international readership were highly regarded. Based on the findings of this study the potential of OADJ was discussed, as were suggestions for enhancing the OADJ environment.

Society is experiencing a global shift in which older people now outnumber children five years and younger in many countries. This demographic aging has profound implications for library and information professionals, and yet research into the information needs of older adults – especially from diverse backgrounds – remains underdeveloped. This study seeks to help address this gap by studying the aging-related information needs and barriers of LGBT+ older adults. Interviews with 25 LGBT+ older adults in East Tennessee were analyzed using thematic analysis to identify five need (e.g., culturally competent care, LGBT+ specific services, social support, planning, and caregiver services) and seven barrier (e.g., stigma, discrimination, fewer personal resources, identity concealment, staff limitations, personality, ageism and elder abuse) themes. Beyond the aging focus, the study brings attention to the need for more research on intersectional populations in general and offers one of the first – perhaps only – studies of the information needs of LGBT+ older adults. It also presents a challenge to librarians and other information professionals in considering how to fight inequities for intersectional populations. Future research will consider how to meet needs and address the barriers LGBT+ older adults face.

Factors influencing Chinese graduate students’ adoption of AI-generated content (AIGC) tools are examined through partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The developed AIGCT-SI model incorporates key elements such as information accuracy, trust, and privacy concerns. PLS-SEM results indicate that performance expectancy, effort expectancy, facilitating conditions, and habit significantly impact students’ intentions, with trust acting as a key mediator, particularly for privacy concerns and social influence. FsQCA reveals seven configurations, demonstrating how combinations of performance expectancy, effort expectancy, and facilitating conditions drive adoption. A bidirectional relationship between privacy concerns and trust is observed, with trust mitigating privacy risks in several configurations. This integrative approach highlights the complex dynamics of AIGC tool adoption and provides strategic insights for their effective use in Chinese graduate education. As the findings are based on the Chinese context, further exploration in other educational settings is encouraged to validate their broader applicability.

Poetry was a unique literary genre in ancient China as an important way to express sentiments. Chinese ancient poetry not only has simple words, strict meters and rich semantic relationships, but also widely uses rhetorical techniques such as simile and personification, as well as metaphorical means such as allusion and imagery, which makes it difficult to understand their implicit sentiments quickly and accurately. Therefore, this paper attempts to make full use of the semantic features of Chinese ancient poetry text and the knowledge feature of related domains under the guidance of the research paradigm of digital intelligence integration, and based on which, proposed Sentiment Analysis Model of Chinese Ancient Poetry based on Multidimensional Attention (SAMCAP). This model extracts semantic features from Chinese ancient poetry text, meanwhile designs a multidimensional attention to extract the knowledge feature from the knowledge base of Chinese ancient poetry. The recognition of Chinese ancient poetry sentiment is performed by integrating the textual feature and knowledge feature. Comparison experiments on the open ancient poetry corpus verified the effectiveness of the proposed model, and the ablation experiment explored the importance of different knowledge to the sentiment analysis result of Chinese ancient poetry.