Large-Scale Analysis of the Accuracy of the Journal Classification Systems of Web of Science and Scopus

Journal classification systems play an important role in bibliometric analyses. The two most important bibliographic databases, Web of Science and Scopus, each provide a journal classification system. However, no study has systematically investigated the accuracy of these classification systems. To examine and compare the accuracy of journal classification systems, we define two criteria on the basis of direct citation relations between journals and categories. We use Criterion I to select journals that have weak connections with their assigned categories, and we use Criterion II to identify journals that are not assigned to categories with which they have strong connections. If a journal satisfies either of the two criteria, we conclude that its assignment to categories may be questionable. Accordingly, we identify all journals with questionable classifications in Web of Science and Scopus. Furthermore, we perform a more in-depth analysis for the field of Library and Information Science to assess whether our proposed criteria are appropriate and whether they yield meaningful results. It turns out that according to our citation-based criteria Web of Science performs significantly better than Scopus in terms of the accuracy of its journal classification system

TINJAUAN PUSTAKA SISTEMATIS PADA BASIS DATA PUSTAKA DIGITAL: TREN RISET, METODOLOGI, DAN COVERAGE FIELDS

The characterization of digital databases is needed to make it easier for academics to identify scientific literature properly and efficiently. This literature review intends to provide characterizations and descriptions related to research trends, methods and coverage fields studied in research related to the scientific database of scientific literature from around 2007 to the present (January 2019). By applying the specified inclusion and exclusion criteria, 54 relevant studies were chosen to be studied further. The systematic literature review method was applied in this study to analyze and identify previous studies related to this topic. Based on the selected primary literature there is an increasing trend of studies related to the scientific database of scientific literature. In addition, we can see that there are four of the most influential and influential publication journals related to this topic, namely the Journal of Informetrics, Journal of Cleaner Production, Asian Social Science and Journal of Academic Librarianship which are characterized by high levels of productivity issues related to the topics studied and SJR values rank is in the range Q1. Most of the studies were conducted on Scopus digital database (41%), Web of Sciences (WoS) 38% and Google Scholar (GS) 13% and the rest spread in other publication journals. The results of this study also identified that Scopus is a scientific database which has the most varied coverage fields compared to other digital database scientific literature. WoS is a digital database of scientific literature that has proven to have a paper with a higher impact factor than others. GS has the predicate digital database with the largest collection level

How Multidisciplinary is Gamification Research? : Results from a Scoping Review

Gamification has been repeatedly framed as an emerging multidisciplinary research field. However, it is unclear how multidisciplinary the field actually is. To answer this question, this paper presents initial results of a broader scoping review of gamification research published between 2010 and 2016. Close to 2,000 peer-reviewed English-language journal and conference papers were identified across 11 databases and categorized by discipline. Results indicate an explosive growth of literature peaking in 2015. Early on, Information and Computing Science dominated the field, to be overtaken by the sum of other disciplines in 2013, education, economics and tourism in specific. This indicates that gamification was initially a field within computer science and HCI and has only recently become truly multi-disciplinary

Does female-authored research have more educational impact than male-authored research?

This is an accepted manuscript of an article published by Levy Library Press in Journal of Altmetrics on 04/10/2018, available online: http://doi.org/10.29024/joa.2 The accepted version of the publication may differ from the final published version.Female academics are more likely to be in teaching-related roles in some countries, including the USA. As a side effect of this, female-authored journal articles may tend to be more useful for students. This study assesses this hypothesis by investigating whether female first-authored research has more uptake in education than male first-authored research. Based on an analysis of Mendeley readers of articles from 2014 in five countries and 100 narrow Scopus subject categories, the results show that female-authored articles attract more student readers than male-authored articles in Spain, Turkey, the UK and USA but not India. They also attract fewer professorial readers in Spain, the UK and the USA, but not India and Turkey, and tend to be less popular with senior academics. Because the results are based on analysis of differences within narrow fields they cannot be accounted for by females working in more education-related disciplines. The apparent additional educational impact for female-authored research could be due to selecting more accessible micro-specialisms, however, such as health-related instruments within the instrumentation narrow field. Whatever the cause, the results suggest that citation-based research evaluations may undervalue the wider impact of female researchers

Construction of a Pragmatic Base Line for Journal Classifications and Maps Based on Aggregated Journal-Journal Citation Relations

A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category. Nine major fields are distinguished at the top level. Further decomposition of the social sciences is pursued for the sake of example with a focus on journals in information science (LIS) and science studies (STS). The new classification system improves on alternative options by avoiding the problem of randomness in each run that has made algorithmic solutions hitherto irreproducible. Limitations of the new system are discussed (e.g. the classification of multi-disciplinary journals). The system's usefulness for field-normalization in bibliometrics should be explored in future studies.Comment: accepted for publication in the Journal of Informetrics, 20 July 201

Are Mendeley Reader Counts Useful Impact Indicators in all Fields?

Reader counts from the social reference sharing site Mendeley are known to be valuable for early research evaluation. They have strong correlations with citation counts for journal articles but appear about a year before them. There are disciplinary differences in the value of Mendeley reader counts but systematic evidence is needed at the level of narrow fields to reveal its extent. In response, this article compares Mendeley reader counts with Scopus citation counts for journal articles from 2012 in 325 narrow Scopus fields. Despite strong positive correlations in most fields, averaging 0.671, the correlations in some fields are as weak as 0.255. Technical reasons explain most weaker correlations, suggesting that the underlying relationship is almost always strong. The exceptions are caused by unusually high educational or professional use or topics of interest within countries that avoid Mendeley. The findings suggest that if care is taken then Mendeley reader counts can be used for early citation impact evidence in almost all fields and for related impact in some of the remainder. As an additional application of the results, cross-checking with Mendeley data can be used to identify indexing anomalies in citation databases