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Regional disparities in Web of Science and Scopus journal coverage
The two most important citation indexes used by the global science community contain marked regional disparities in their representation of academic journals. Existing work on the geographical coverage of Web of Science and Scopus citation indexes compared their coverage of journals in a small sample of ‘top’ countries. This paper offers the first regional analysis of journal representation in these two indexes across all eight UNESCO world regions, compared to the total number of active Ulrich’s directory academic journals in these regions. Journal lists from 239 countries/territories were collected from Ulrich’s periodical directory and analyzed by region. This enables a comparison of the regional distribution of journals within Web of Science (20,255 matched journals) and Scopus (23,348 matched journals) with those in Ulrich’s directory (83,429 journals). Journals published in Europe, Oceania and North America were more likely to be indexed in Scopus and Web of Science compared to other world regions. Journals published in sub-Saharan Africa were the most underrepresented and were four times less likely to be indexed than those published in Europe. The analysis also offers a quantitative breakdown of journal publication languages, highlighting how Scopus and Web of Science disproportionately index English language publications in all world regions. Finally, the analysis shows how field coverage by Web of Science and Scopus differs between the regions, with the Social Sciences and Humanities still under-represented, in comparison to Natural Sciences and Medical & Health Science.
Journal Article
Cruising the Library
Cruising the Library examines the ways in which library classifications have organized sexuality and sexual perversion. The author studies the Library of Congress Subject Headings and Classification, as well as the Library of Congress's Delta Collection, a restricted collection of obscenity until 1964.
eBook
Identifying interdisciplinary topics and their evolution based on BERTopic
Interdisciplinary topic reflects the knowledge exchange and integration between different disciplines. Analyzing its evolutionary path is beneficial for interdisciplinary research in identifying potential cooperative research direction and promoting the cross-integration of different disciplines. However, current studies on the evolution of interdisciplinary topics mainly focus on identifying interdisciplinary topics at the macro level. More analysis of the evolution process of interdisciplinary topics at the micro level is still needed. This paper proposes a framework for interdisciplinary topic identification and evolutionary analysis based on BERTopic to bridge the gap. The framework consists of four steps: (1) Extract the topics from the dataset using the BERTopic model. (2) Filter out the invalid global topics and stage topics based on lexical distribution and further filter out the invalid stage topics based on topic correlation. (3) Identify interdisciplinary topics based on disciplinary diversity and disciplinary cohesion. (4) Analyze the interdisciplinary topic evolution by inspecting the intensity and content in the evolution, and visualize the evolution using Sankey diagrams. Finally, We conduct an empirical study on a dataset collected from the Web of Science (WoS) in Library & Information Science (LIS) to evaluate the validity of the framework. From the dataset, we have identified two distinct types of interdisciplinary topics in LIS. Our findings suggest that the growth points of LIS mainly exist in the interdisciplinary research topics. Additionally, our analysis reveals that more and more interdisciplinary knowledge needs to be integrated to solve more complex problems. Mature interdisciplinary topics mainly formed from the internal core knowledge in LIS stimulated by external disciplinary knowledge, while promising interdisciplinary topics are still at the stage of internalizing and absorbing the knowledge of other disciplines. The dataset, the code for implementing the algorithms, and the complete experiment results will be released on GitHub at:
https://github.com/haihua0913/IITE-BERT
.
Journal Article
I'll be a librarian
\"Readers follow along on a day in the life of a librarian as a young girl pretends that the family den is a public library. Includes a glossary of library terms and a library scavenger hunt activity\"--Provided by publisher.
Book
ChatGPT is bullshit
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
Journal Article
Visibility, impact, and applications of bibliometric software tools through citation analysis
This study examines the visibility, impact, and applications of bibliometric software tools in the peer-reviewed literature through a “Cited Reference Search” using the Web of Science (WOS) database. A total of 2882 citing research articles to eight bibliometric software tools were extracted from the WOS Core Collection between 2010 and 2021. These citing articles are analyzed by publication year, country, publication title, publisher, open access level, funding agency, and WOS category. Mentions of bibliometric software tools in Author Keywords and KeyWords Plus are also compared. The VOSviewer software is utilized to identify specific research areas by discipline from the keyword co-occurrences of the citing articles. The findings reveal that while bibliometric software tools are making a noteworthy impact and contribution to research, their visibility through referencing, Author Keywords, and KeyWords Plus is limited. This study serves as a clarion call to raise awareness and initiate discussions on the citing practices of software tools in scholarly publications.
Journal Article