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presents the distribution of publication dates found in the bibliographic collection: it contains works published between 1901 and 2008, with the clear majority from the 1960's onward. Since the bibliographic records represent material housed in a science and engineering library they can be assumed to represent typical literature about Science.
Source publication
Maps of scientific knowledge are generally created by analyzing scientific literature including journal articles, conference proceedings, books, and monographs. Although citation analysis is the most popular method for generating maps of science from scientific journal articles and their citations, other relationships between scientific topics can...
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The importance of technical objects maintenance issues takes on particular significance in the area of increasing competition an increasingly higher demands in the area of quality, reliability and productivity of performed system’s functions and tasks. The main objectives of maintenance have evolved for the last fifty years. Thus, the article is ai...
Citations
... In scientometrics field, citation analysis (eg. direct citation, co-citation and bibliographic coupling) is the most popular method to create maps of science from academic journal articles and their citations (Shu et al. 2017). Meantime, different maps of science are generated from units in different granularity (eg. ...
Science mapping (or mapping knowledge domains) has been a hot topic in scientometrics field since 1990s. Science maps are generally created by analyzing different kinds of scientific literatures, including journal articles, conference proceedings, patents, books, and monographs. Citation analysis (eg. direct citation, co-citation, bibliographic coupling and hybrid approach) with units in different granularity (eg. authors, keywords, articles, journals and cate-gories) is the most popular method to create maps of science. In this study, paper-level classification codes of science based on Chinese Library Classification Scheme (CLC) are used to draw global maps of science. Paper-level classification codes of 3,490,665 academic articles published from 2008 to 2018 in 1,687 core Chinese journals indexed by CSSCI (Chinese Social Sciences Citation Index) and CSCD (Chinese Science Citation Database) are harvested and three kinds of approaches (publishing, co-assignments and citing networks with various of interdisciplinary measures) are applied to construct and analyze global maps of science. The novel CLC-based science maps reveal new relations among different disciplines of science in Chinese knowledge organization system, which offers a new way to comprehensively understand the landscape of scientific domains and how they interact.
... thematically or historically). Thus, LCSH co-assignments indicate a relationship between two LCSH terms, as these co-assignments express the likelihood that existing knowledge about two topics will be written about (and read) together in the same work (Shu et al., 2017). In other words, and of particular interest in the present study, is that co-assignment between two level-1 LCSHs represents (or indicates) a relationship between two disciplines. ...
... This method of reassignment effectively propagates co-assigned relationships up the chain of broader terms, and have been used effectively in prior work (e.g. Shu et al. (2017)). ...
... These results provide support to previous claims that co-assigned subject headings express the correlation between existing knowledge while citations emphasize the similarity between disciplines (Leydesdorff et al., 2016;Shu et al., 2017). As measured by LCSH co-assignment, the disparity measures between disciplines are all higher than 0.4000 except for the Biology/Medicine pair. ...
Examining the relationships among scientific disciplines is important today, but existing methods are limited by the contents and structure of their bibliographic databases. We therefore demonstrate a novel approach that measures disparity by examining the organization of published scientific books and monographs into Library of Congress Subject Headings. After outlining the method and analyses conducted, we compare our results with those produced by prior works, note potential implications of the demonstrated method for use by bibliometric practitioners, and suggest directions for further research.
... Suominen and Toivanen generated a map of science using topic modeling based on latent patterns in texts retrieved from Web of Science (WoS) [14]. Also, Shu et al. produced a map of science based on nonfiction books and their Library of Congress Subject Headings (LCSH) coassignments [15]. ...
... Some of these assigned MeSH terms are designated as major, indicating an article's primary topics, whereas the others represent topics only discussed in the article. MeSH co-assignments can be used as a measure of the relative strength of the relationship between two MeSH terms, as these co-assignments express the likelihood that existing knowledge about two medical topics will be read together in the same article [15]. Thus a map of biomedical sciences can be generated on the basis of MeSH co-assignments. ...
... Assigned MeSH terms at level 3 or lower were reassigned to their parent level 2 or grandparent level 1 MeSH terms. For example, for the hierarchical structure of Organisms/Eukaryota/Animals/Invertebrates/Arthropods/Insect a/Pterygota/Neoptera/Holometabola/Diptera/Nematocera/Culico morpha/Culicidae/Aedes, the MeSH terms Animals, Invertebrates, Arthropods, Insecta, Pterygota, Neoptera, Holometabola, Diptera, Nematocera, Culicomorpha, Culicidae, and Aedes were reassigned to Organisms (level 1) or Eukaryota (level 2) when producing the MeSH co-assignment map at level 1 or 2. This method of reassignment to broader or more general abstraction levels has been used in previous studies of library classification mapping, which have confirmed its robustness [15]. ...
Objective:
This study compares two maps of biomedical sciences using Medical Subject Headings (MeSH) term co-assignments versus MeSH terms of citing/cited articles and reveals similarities and differences between the two approaches.
Methods:
MeSH terms assigned to 397,475 journal articles published in 2015, as well as their 4,632,992 cited references, were retrieved from Web of Science and MEDLINE databases, respectively, which formed over 7 million MeSH co-assignments and nearly 18 million direct citation pairs. We generated six network visualizations of biomedical science at three levels using Gephi software based on these MeSH co-assignments and citation pairs.
Results:
The MeSH co-assignment map contained more nodes and edges, as MeSH co-assignments cover all medical topics discussed in articles. By contrast, the MeSH citation map contained fewer but larger nodes and wider edges, as citation links indicate connections to two similar medical topics.
Conclusion:
These two types of maps emphasize different aspects of biomedical sciences, with MeSH co-assignment maps focusing on the relationship between topics in different categories and MeSH direct citation maps providing insights into relationships between topics in the same or similar category.
... As it is the case for citation (Kim and Barnett, 2008) and collaboration networks (Ding, 2011), keyword-based bibliometric analyses and social network analysis were also combined in multiple studies (Bodlaj and Batagelj, 2014;Hu et al., 2013;Su and Lee, 2010), for example, to create complex co-keyword networks and keywords co-occurrence networks (Cheng et al., 2018;Kastrin et al., 2014;Li et al., 2016). Yet recently, subject headings are still used separately for mapping science (Shu et al., 2017), to detect journal similarity (Yan and Chien, 2021) or in combination with cocitation and other metrics (Cabeza Ramrez et al., 2019). Due to the establishment of network analysis on content networks, their characteristics are now studied intensely (Tang et al., 2020) in multiple fields (Wang, 2018) together with other state-of-the-art techniques such as topic models (Leydesdorff and Nerghes, 2017). ...
Based on a literature review, we present a framework for structuring the application of graph theory in the library domain. Our goal is to provide both researchers and libraries with a standard tool to classify scientific work, at the same time allowing for the identification of previously underrepresented areas where future research might be productive. To achieve this, we compile graph theoretical approaches from the literature to consolidate the components of our framework on a solid basis. The extendable framework consists of multiple facets grouped into five categories whose elements can be arbitrarily combined. Libraries can benefit from these facets by using them as a point of reference for the (meta)data they offer. Further work on formally defining the framework’s categories as well as on integration of other graph-related research areas not discussed in this article (e.g. knowledge graphs) would be desirable and helpful in the future.
... later, sapon-white and hansbrough [9] showed that the dissertations with subject headings are found to be more likely to circulate than those without subject headings. Some researchers have also studied subject heading for various purposes, such as: analysing subjects listed in different subject heading [10]- [12], generating map of science [13], [14], developing simplified subject heading list [15], [16], and assigning subject heading automatically [17]- [19]. ...
Subject heading is a controlled vocabulary that describes the topic of adocument, which is important to find and organize library resources. Assigning appropriate subject headings to a document, however, is a time-consuming process. We therefore conduct a novel study on the effectiveness of information retrieval models, i.e.,language model (LM) andvector spacemodel (VSM), to automatically generate a ranked list of relevant subject headings, with the aim to give a recommendation for librarians to determine the subject headings effectively and efficiently. Our results show that there are a high number of our queries (up to 61%) that have relevant subject headings in the ten top-ranked recommendations and on average, the first relevant subject heading is found at the early position (3rd rank). This indicates that document retrieval methods can help the subject heading assignment process. LM and VSM are shown to have comparable performance, except when the search unit is title, VSM is superior to LM by8-22%. Our further analysis exhibits three faculty pairs that are potential to have research collaboration as their students’ thesis often have overlap subject headings: i) economy and business-social and political sciences, ii) nursing-public health and iii) medicine-public health.</p
... A similar notion comes up on the basis of investigating the co-occurrence of shared concepts in books and monographs. Such results too show the importance of medicine and physics as well as chemistry and mathematics to all branches of natural sciences, demonstrating the importance of those sciences for many other disciplines [65]. ...
Understanding about nature of science is important topic in science education as well as in pre-service science teacher education. In science education, Nature of Science (NOS), in its different forms of educational scaffoldings, seeks to provide with students an understanding of features of scientific knowledge and science in general, how scientific knowledge changes and becomes accepted, and what factors guide scientific activities. For a science teacher, deep and broad enough picture of sciences is therefore of importance. This study attempts to show that the research field called Science of Science (SoS) can significantly support building such a panoramic picture of sciences, and through that, significantly support NOS. The SoS approaches the structure and dynamics of science quantitatively, using scientific documents (e.g. publications, reports, books and monographs and patent applications) as trails to map the landscape of sciences. It is argued here that SoS may provide material and interesting cases for NOS, and in so doing enrich NOS in a similarly significant way as history, philosophy and sociology of science (HPSS) scholarship has done thus far. This study introduces several themes based on SoS that are of relevance for NOS as they were introduced and discussed in a pre-service science teachers' course. The feedback from pre-service teachers shows that introducing SoS, with minimal additional philosophical interpretations and discussions, but simply as evidential facts and findings, sparks ideas and views that come very close to NOS themes and topics. Discussions related to nature of science, and specific educational NOS scaffoldings for it, can find a good companion in SoS; the latter providing facts and evidence of thee structure and dynamics of sciences, the former providing perspectives for interpretations.
... Scaling reached 100 to make the graph sparser. Then, algorithm by Yifan Hu multilevel (Shu et al., 2017) is used to lay out the process and optimize for graph readability. It is force-directed and multilevel and complexity for O (N Ã log (N)). ...
Purpose
Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks.
Design/methodology/approach
This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals.
Findings
The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet.
Social implications
The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.
Originality/value
This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”
... The Library of Science [14] maintains a controlled vocabulary, Library of Science Subject Headings (LCSH) with the purpose of collecting and organizing bibliographical knowledge. LCSH is generally accepted as a standard classification system of subjects due to its widespread availability and ease of use [26]. The hierarchical structure of LCSH can be used in evaluating curricular coherence because it can reveal existing relations between the disciplines of science that are addressed in science and technology courses. ...
An effective and highly efficient curriculum is the foundation of an optimal content delivery to students and may lead to the success of the academic program. Ensuring the effectiveness of curricular processes goes beyond the successful design of individual courses and it is subject to careful planning in accordance to appropriate policies and procedures that enable a high level of curriculum coherence. Such curriculum can guarantee that students are presented with a complete set of interrelated topics related to the area of study that can enable students to connect topics in individual courses and apply them in professional settings. The goal of this article is to evaluate the curriculum coherence of an Information Science program using ontologies and natural language processing techniques. Curricular coherence is evaluated using a possibilistic approach which evaluates academic gaps and overlaps that exist in the core courses offered in the degree. The use of ontologies enables us to perform a qualitative study of curricular coherence at different levels of ontological abstraction using mereotopological principles. The knowledge inferred from this process can be used at the universities to optimize their course offering and content for better academic content.
... Assigned MeSH terms at level 3 or lower were re-assigned to their parent level-2 or grandparent level-1 MeSH terms. This method of reassignment to broader or more general abstraction levels, has been used in library classification mapping where its robustness has been confirmed (Shu et al., 2017). Table 2, four datasets were finalized to produce four maps of life science: MeSH co-assignment map at level 1, MeSH co-assignment map at level 2, MeSH citation map at level 1, MeSH citation map at level 2. For each dataset, MeSH terms as well as their co-assignments or citation pairs (major MeSH terms between citing and cited papers) were imported into graphdrawing software Gephi to generate the visual map of life science. ...
Maps of scientific knowledge are generally based on citation analysis and therefore reveal how disciplines draw from each other to produce new knowledge. Although subject headings as well as their co-assignments represent the topics and their relationships within the journal article or book, they rarely have been used for mapping science. This study attempts to map the life science based on the Medical Subject Headings (MeSH) as well as their co-assignment at the paper level, which could advance the knowledge in mapping science.
... Already in 1975, Garfield, Malin, andSmall (1975) introduced an automatic classification system of science that could classify papers on the basis of their citation patterns. Following this, several studies have constructed paper classification systems in which publications are clustered into disciplines based on citation analysis techniques such as direct citation, bibliographic coupling, co-citation and hybrid methods (Shu, Dinneen, Asadi, & Julien, 2017). These provide measures of document similarity where documents judged adequately similar (e.g., 95% similar) are grouped to form a structure of science (Griffith, Small, Stonehill, & Dey, 1974;Small & Griffith, 1974). ...
... Although the U.S. Library of Congress classification (LCC) 4 is the most widely-accepted classification system, it is used predominantly in research and academic libraries to classify physical books and monographs into a single discipline for the purpose of establishing a unique address on a shelf for that book, rather than classifying journal articles. Shu et al. (2017) present a methodology that classifies the scientific literature into disciplines of the Library of Congress Subject Headings (LCSH), but LCSH is not applied at the paper-level. Medical Subject Headings (MeSH) 5 is a candidate classification since it is applied to both journal articles and books, but findings based on this single domain classification are difficult to generalize to disciplines beyond the medical sciences. ...
... For example, the paper assigned to the level-2 discipline Science & Science Studies (G3) was re-assigned to the level-1 discipline Culture, Science, Education & Sports (G), since the former is not included in the list of 66 level- 2 disciplines. This method of reassignment to broader or more general abstraction levels, has been used in library classification mapping where its robustness has been confirmed ( Shu et al., 2017). Finally, 11 level-1 disciplines in social science and humanities were merged to two level-1 disciplines: General Social Science corresponding to CLC codes starting with B, C, D, E, F, G and Arts and Humanities 14 corresponding to CLC codes starting with A, H, I, J, K. ...
The classification of science into disciplines is at the heart of bibliometric analyses. While most classifications systems are implemented at the journal level, their accuracy has been questioned, and paper-level classifications have been considered by many to be more precise. However, few studies investigated the difference between journal and the paper classification systems. This study addresses this gap by comparing the journal- and paper-level classifications for the same set of papers and journals. This isolates the effects of classification precision (i.e., journal- or paper-level) to reveal the extent of paper misclassification. Results show almost half of papers could be misclassified in journal classification systems. Given their importance in the construction and analysis of bibliometric indicators, more attention should be given to the robustness and accuracy of these disciplinary classifications schemes.
