Meta-synthesis in Library &amp; Information Science Research

Xie, Juan; Ke, Qing; Cheng, Ying; Everhart, Nancy

doi:10.1016/j.acalib.2020.102217

Cited by 6 publications

(2 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They noted that a lack of sufficient LIS quantitative studies limits the applicability of meta‐analysis for many LIS research topics but made recommendations for effective use of the method when it can be applied. Xie et al (2020) analyzed 44 LIS‐related meta‐synthesis studies in terms of contribution, meta‐synthesis methodology, and research topics. They found that meta‐synthesis research has only been conducted on a limited number of topics: health informatics, information behavior, library user services, information literacy, e‐government, human–computer interaction, information systems, and information management.…”

Section: Research Opportunities For Information Sciencementioning

confidence: 99%

Reviews and Reviewing: Approaches to Research Synthesis. An Annual Review of Information Science and Technology (ARIST) paper

Smith

2023

Asso for Info Science & Tech

View full text Add to dashboard Cite

Reviews have long been recognized as among the most important forms of scientific communication. The rapid growth of the primary literature has further increased the need for reviews to distill and interpret the literature. This review on Reviews and Reviewing: Approaches to Research Synthesis encompasses the evolution of the review literature, taxonomy of review literature, uses and users of reviews, the process of preparing reviews, assessment of review quality and impact, the impact of information technology on the preparation of reviews, and research opportunities for information science related to reviews and reviewing. In addition to providing a synthesis of prior research, this review seeks to identify gaps in the published research and to suggest possible future research directions.

show abstract

Section: Research Opportunities For Information Sciencementioning

confidence: 99%

Reviews and Reviewing: Approaches to Research Synthesis. An Annual Review of Information Science and Technology (ARIST) paper

Smith

2023

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

“…In 2003, the Chinese Academy of Sciences Documentation and Intelligence Center in the field of professional libraries established the subject librarian system [3][4][5]. In September 2008, research libraries such as Shanghai Jiaotong University Library and Zhejiang University Library also started to introduce subject services [6][7]. Domestic university libraries have set up a "subject librarian system"; the implementation of subject services won the readers widespread praise [8].…”

Section: Introductionmentioning

confidence: 99%

Cloud Data Resources and Library Subject Information Services

Zhang

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In the evolving landscape of library services, propelled by advancements in Internet technology and service paradigms, this study utilizes cloud-based lending data from college libraries to improve user profiling and subject-specific lending. Integrating the K-means algorithm with a Boolean matrix-enhanced Apriori algorithm, we devise a data mining model that fine-tunes detecting patterns in user borrowing behaviors. This approach distinguishes five distinct subject areas: energy, computing, electronic communication, machinery, and environmental chemistry. The outcome reveals a bibliographic association rule mining confidence of up to 79.38%, a 30% increase over conventional methods. Moreover, it generates three notable 2-item sets. Our model introduces a groundbreaking way to offer personalized library services, significantly enriching the user experience with tailored subject information.

show abstract