The evolution and shift of research topics and methods in library and information science

Themes in Health Sciences Librarianship Literature, 2016-2020: A Keyword and Subject Analysis

Previous investigations into trends in Library and Information Science literature have revealed changes in the topics librarians publish on over time, with older studies highlighting classification and indexing, and information retrieval and more recent studies highlighting keywords such as Internet, information technology, digital libraries, and again, information retrieval. No similar investigation has been conducted on current publication trends by health sciences librarians. This study analyzes the top themes on which health sciences librarians published from 2016 to 2020 by examining the frequency of keywords. Keywords and subject headings were analyzed from The Journal of the Medical Library Association, Medical References Services Quarterly, The Journal of Hospital Librarianship, and The Journal of Electronic Resources in Medical Libraries. A total of 8,806 keywords were downloaded for analysis and organized into 292 categories during taxonomy creation. The ten most frequent themes were: libraries, information, education, humans, demography, librarian, geographical locations, research, electronic resources, and technology. The study also found that data, psychiatry and psychology, informatics, and publishing were other key themes, indicating that health sciences librarians are publishing on a wide range of topics. Some keywords that appeared only once, such as telecommuting and flexible staffing, suggest emerging areas of research for librarians.

Data mining topics in the discipline of library and information science: analysis of influential terms and Dirichlet multinomial regression topic model

Purpose

The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to identify data mining related subject terms and topics in representative LIS scholarly publications.

Design/methodology/approach

A large set of bibliographic records over 38,000 was collected from a scholarly database representing the fields of LIS and the data mining, respectively. A multitude of text mining techniques were applied to investigate prevailing subject terms and research topics, such as influential term analysis and Dirichlet multinomial regression topic modeling.

Findings

The findings of this study revealed the relationship between the LIS and data mining research domains. Various data mining method terms were observed in recent LIS publications, such as machine learning, artificial intelligence and neural networks. The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.

Originality/value

This investigation is one of a few studies that empirically investigated the relationships between the LIS and data mining research domains. Multiple text mining techniques were employed to delineate to which extent the two research domains would be associated with each other based on both at the term-level and topic-level analysis. Methodologically, the study identified influential terms in each domain using multiple feature selection indices. In addition, Dirichlet multinomial regression was applied to explore LIS topics in relation to data mining.

What Does Information Science Offer for Data Science Research?: A Review of Data and Information Ethics Literature

This paper reviews literature pertaining to the development of data science as a discipline, current issues with data bias and ethics, and the role that the discipline of information science may play in addressing these concerns. Information science research and researchers have much to offer for data science, owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral perspectives to issues within natural science disciplines. Information science researchers have already contributed to a humanistic approach to data ethics within the literature and an emphasis on data science within information schools all but ensures that this literature will continue to grow in coming decades. This review article serves as a reference for the history, current progress, and potential future directions of data ethics research within the corpus of information science literature.

Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers

Scientific activity has become increasingly complex in recent years. The need for international research collaboration has thus become a common pattern in science. In this current landscape, countries face the problem of maintaining their competitiveness while cooperating with other countries to achieve relevant research outputs. In this international context, publications from international collaborations tend to achieve greater scientific impact than those from domestic ones. To design policies that improve the competitiveness of countries and organizations, it thus becomes necessary to understand the factors and mechanisms that influence the benefits and impact of international research. In this regard, the aim of this study is to confirm whether the differences in impact between international and domestic collaborations are affected by their topics and structure. To perform this study, we examined the Library and Information Science category of the Web of Science database between 2015 and 2019. A science mapping analysis approach was used to extract the themes and their structure according to collaboration type and in the whole category (2015–2019). We also looked for differences in these thematic aspects in top countries and in communities of collaborating countries. The results showed that the thematic factor influences the impact of international research, as the themes in this type of collaboration lie at the forefront of the Library and Information Science category (e.g., technologies such as artificial intelligence and social media are found in the category), while domestic collaborations have focused on more well-consolidated themes (e.g., academic libraries and bibliometrics). Organizations, countries, and communities of countries must therefore consider this thematic factor when designing strategies to improve their competitiveness and collaborate.

Largest contribution to LIS by external disciplines as measured by the characteristics of research articles

The paper analyses Library and Information Science (LIS) articles published in leading international LIS journals based on their authors’ disciplinary backgrounds. The study combines content analysis of articles with authors’ affiliation analysis. The main research question is: Are authors’ disciplinary backgrounds associated with choice of research topics and methods in LIS articles? The study employs a quantitative content analysis of articles published in 30 + scholarly LIS journals in 2015, focusing on research topics and methods. The articles are also assigned to three disciplinary categories based on authors’ affiliations: External (no authors from LIS institutions), Internal (all authors from LIS institutions), and Mixed (some authors from LIS institutions, some from outside). The association of articles’ disciplinary categories with article research topics and methods is analysed quantitatively. Most research contributions to LIS come from external articles (57%). However, LIS scholars have a clear majority in research on L&I services and institutions (68%), while external scholars dominate the contributions in Information retrieval (73%) and Scientific communication (Scientometrics, 69%). Internal articles tend to have an intermediary’s (29%) or end-user’s (22%) viewpoint on information dissemination while the external ones have developer’s viewpoint (27%) or no dissemination viewpoint (49%). Among research strategies, survey (29%) and concept analysis (23%) dominate internal articles, survey (28%) and citation analysis (19%) dominate mixed articles, and survey (20%) and citation analysis (19%) dominate external articles. The application profiles of research strategies varied somewhat between disciplinary categories and main topics. Consequently, the development of LIS in the areas of Information retrieval, Information seeking, and Scientific communication seems highly dependent on the contribution of other disciplines. As a small discipline, LIS may have difficulties in responding to the challenges of other disciplines interested in research questions in these three areas.

A comparison of information behavior studies in United States and India: Number of publications, authorship, journals, theories, research populations, and methods

This study compares attributes (authors, journals, populations, theories, methods) of information seeking behavior studies based in the United States and India, based on a search of published articles from 2011 to 2020 in relevant information science databases. The findings indicate major differences in information behavior research among the two countries. Information behavior research in the United States tends to focus more on health and medicine-related research populations, employ greater use of information behavior theories, and use a variety of quantitative and qualitative research methods (as well as mixed methods). Information behavior research in India tends to focus more on general populations, use less theory, and rely heavily on quantitative research methods—particularly questionnaires (88% of studies). These findings suggest a healthy and intellectually-diverse information behavior research area in the United States and ample room for growth of the research area within India.

Not a token! A discussion on racial capitalism and its impact on academic librarians and libraries

Purpose

The purpose of this article is to introduce the concept of racial capitalism in the context of academic libraries.

Design/methodology/approach

This paper draws on Leong's (2013) extended theory of racial capitalism and identifies how neoliberalism and racial capitalism are tied as well as how it is manifested in academic libraries through tokenism, racialized tasks, consuming racial trauma, cultural performance demands, workload demands and pay inequity.

Findings

The article ends with some suggestions in how to address these problematic practices though dismantling meritocratic systems, critical race theory in LIS education and training, and funding EDI work.

Originality/value

The article explores a concept in the academic library context and points to practices and structures that may commodify racialized identities.