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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.

Clarivate Analytics’ Web of Science Core Collection, a comprehensive database consisting of ten sub-datasets, is increasingly applied in academic research across over two hundred Web of Science categories. 271 English language SCIE and SSCI papers published in 2017–2018 from the category of Information Science and Library Science have mentioned “Web of Science” in the topic field. A manual check of the full texts of these papers reveals that 243 of them have used “Web of Science Core Collection” as the data source but over half of them haven’t specified the sub-datasets of Web of Science Core Collection used in the study. Since many institutions may only subscribe to a customized subset of the whole core collection, the non-transparency of the data source will hinder the reproducibility of some corresponding studies. This study suggests that researchers should specify the sub-datasets and corresponding coverage timespans when using Web of Science Core Collection as the data source.

Traditionally, Web of Science and Scopus have been the two most widely used databases for bibliometric analyses. However, during the last few years some new scholarly databases, such as Dimensions, have come up. Several previous studies have compared different databases, either through a direct comparison of article coverage or by comparing the citations across the databases. This article aims to present a comparative analysis of the journal coverage of the three databases (Web of Science, Scopus and Dimensions), with the objective to describe, understand and visualize the differences in them. The most recent master journal lists of the three databases is used for analysis. The results indicate that the databases have significantly different journal coverage, with the Web of Science being most selective and Dimensions being the most exhaustive. About 99.11% and 96.61% of the journals indexed in Web of Science are also indexed in Scopus and Dimensions, respectively. Scopus has 96.42% of its indexed journals also covered by Dimensions. Dimensions database has the most exhaustive journal coverage, with 82.22% more journals than Web of Science and 48.17% more journals than Scopus. This article also analysed the research outputs for 20 selected countries for the 2010–2018 period, as indexed in the three databases, and identified database-induced variations in research output volume, rank, global share and subject area composition for different countries. It is found that there are clearly visible variations in the research output from different countries in the three databases, along with differential coverage of different subject areas by the three databases. The analytical study provides an informative and practically useful picture of the journal coverage of Web of Science, Scopus and Dimensions databases.

New sources of citation data have recently become available, such as Microsoft Academic, Dimensions, and the OpenCitations Index of CrossRef open DOI-to-DOI citations (COCI). Although these have been compared to the Web of Science Core Collection (WoS), Scopus, or Google Scholar, there is no systematic evidence of their differences across subject categories. In response, this paper investigates 3,073,351 citations found by these six data sources to 2,515 English-language highly-cited documents published in 2006 from 252 subject categories, expanding and updating the largest previous study. Google Scholar found 88% of all citations, many of which were not found by the other sources, and nearly all citations found by the remaining sources (89–94%). A similar pattern held within most subject categories. Microsoft Academic is the second largest overall (60% of all citations), including 82% of Scopus citations and 86% of WoS citations. In most categories, Microsoft Academic found more citations than Scopus and WoS (182 and 223 subject categories, respectively), but had coverage gaps in some areas, such as Physics and some Humanities categories. After Scopus, Dimensions is fourth largest (54% of all citations), including 84% of Scopus citations and 88% of WoS citations. It found more citations than Scopus in 36 categories, more than WoS in 185, and displays some coverage gaps, especially in the Humanities. Following WoS, COCI is the smallest, with 28% of all citations. Google Scholar is still the most comprehensive source. In many subject categories Microsoft Academic and Dimensions are good alternatives to Scopus and WoS in terms of coverage.

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.

Bibliometric methods or “analysis” are now firmly established as scientific specialties and are an integral part of research evaluation methodology especially within the scientific and applied fields. The methods are used increasingly when studying various aspects of science and also in the way institutions and universities are ranked worldwide. A sufficient number of studies have been completed, and with the resulting literature, it is now possible to analyse the bibliometric method by using its own methodology. The bibliometric literature in this study, which was extracted from Web of Science, is divided into two parts using a method comparable to the method of Jonkers et al. (Characteristics of bibliometrics articles in library and information sciences (LIS) and other journals, pp. 449–551, 2012: The publications either lie within the Information and Library Science (ILS) category or within the non-ILS category which includes more applied, “subject” based studies. The impact in the different groupings is judged by means of citation analysis using normalized data and an almost linear increase can be observed from 1994 onwards in the non-ILS category. The implication for the dissemination and use of the bibliometric methods in the different contexts is discussed. A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact. A noticeable shift is observed in those countries which contribute to the pool of bibliometric analysis, as well as a self-perpetuating effect in giving and taking references.

This study investigated the evolution of library and information science (LIS) by analyzing research topics in LIS journal articles. The analysis is divided into five periods covering the years 1996–2019. Latent Dirichlet allocation modeling was used to identify underlying topics based on 14,035 documents. An improved data-selection method was devised in order to generate a dynamic journal list that included influential journals for each period. Results indicate that (a) library science has become less prevalent over time, as there are no top topic clusters relevant to library issues since the period 2000–2005; (b) bibliometrics, especially citation analysis, is highly stable across periods, as reflected by the stable subclusters and consistent keywords; and (c) information retrieval has consistently been the dominant domain with interests gradually shifting to model-based text processing. Information seeking and behavior is also a stable field that tends to be dispersed among various topics rather than presented as its own subject. Information systems and organizational activities have been continuously discussed and have developed a closer relationship with e-commerce. Topics that occurred only once have undergone a change of technological context from the networks and Internet to social media and mobile applications.

Journal field classifications in Scopus are used for citation-based indicators and by authors choosing appropriate journals to submit to. Whilst prior research has found that Scopus categories are occasionally misleading, it is not known how this varies for different journal types. In response, we assessed whether specialist, cross-field and general academic journals sometimes have publication practices that do not match their Scopus classifications. For this, we compared the Scopus narrow fields of journals with the fields that best fit their articles’ titles and abstracts. We also conducted qualitative follow-up to distinguish between Scopus classification errors and misleading journal aims. The results show sharp field differences in the extent to which both cross-field and apparently specialist journals publish articles that match their Scopus narrow fields, and the same for general journals. The results also suggest that a few journals have titles and aims that do not match their contents well, and that some large topics spread themselves across many relevant fields. Thus, the likelihood that a journal’s Scopus narrow fields reflect its contents varies substantially by field (although without systematic field trends) and some cross-field topics seem to cause difficulties in appropriately classifying relevant journals. These issues undermine citation-based indicators that rely on journal-level classification and may confuse scholars seeking publishing venues.

The majority of academic papers are scarcely cited while a few others are highly cited. A large number of studies indicate that there are many factors influencing the number of citations. An actual review is missing that provides a comprehensive review of the factors predicting the frequency of citations. In this review, we performed a search in WoS, Scopus, PubMed and Medline to retrieve relevant papers. In overall, 2087 papers were retrieved among which 198 relevant papers were included in the study. Three general categories with twenty eight factors were identified to be related to the number of citations: Category one: “paper related factors”: quality of paper; novelty and interest of subject; characteristics of fields and study topics; methodology; document type; study design; characteristics of results and discussion; use of figures and appendix in papers; characteristics of the titles and abstracts; characteristics of references; length of paper; age of paper; early citation and speed of citation; accessibility and visibility of papers. Category two: “journal related factors”: journal impact factor; language of journal; scope of journal; form of publication. Category three: “author(s) related factors”: number of authors; author’s reputation; author’s academic rank; self-citations; international and national collaboration of authors; authors’ country; gender, age and race of authors; author’s productivity; organizational features; and funding. Probably some factors such as the quality of the paper, journal impact factor, number of authors, visibility and international cooperation are stronger predictors for citations, than authors’ gender, age and race; characteristics of results and discussion and so on.

Citation analysis has been a prevalent method in the field of information science, especially research on bibliometrics and evaluation, but its validity relies heavily on how the citations are treated. It is essential to study authors’ citing motivations to identify citations with different values and significance. This study applied a meta-synthesis approach to establish a new holistic classification of citation motivations based on previous studies. First, we used a four-step search strategy to identify related articles on authors’ citing motivations. Thirty-eight primary studies were included after the inclusion and exclusion criteria were applied and appraised using the Evidence-based Librarianship checklist. Next, we decoded and recoded the citing motivations found in the included studies, following the standard procedures of meta-synthesis. Thirty-five descriptive concepts of citation motivations emerged, which were then synthesized into 13 analytic themes. As a result, we proposed a comprehensive classification, including two main categories of citing reasons, i.e., “scientific motivations” and “tactical motivations.” Generally, the citations driven by scientific motivations serve as a rhetorical function, while tactical motivations are social or benefit-oriented and not easily captured through text-parsing. Our synthesis contributes to bibliometric and scientific evaluation theory. The synthesized classification also provides a comprehensive and unified annotation schema for citation classification and helps identify the useful mentions of a reference in a citing paper to optimize citation- based measurements.