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Modern Applied Statistics With S

Social Network Analysis

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

A review of the literature on citation impact indicators

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.

The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis

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 attempts to compare the journal coverage of the three databases: Web of Science, Scopus and Dimensions. The most recent master journal lists of the three databases have been used for the purpose of identifying the overlapping and unique journals covered in the databases. 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 coverage, with 82.22% more journals covered as compared to Web of Science and 48.17% more journals covered as compared to Scopus. We also analysed the research outputs for 20 highly productive countries for the 2010-2019 period, as indexed in the three databases, and identified database-induced variations in research output volume, rank and global share of different countries. In addition to variations in overall coverage of research output from different countries, the three databases appear to have differential coverage of different disciplines.

The Journal Coverage of Web of Science, Scopus and Dimensions: A Comparative Analysis.

Purpose – The purpose of this paper is to discuss the new scientific search service Google Scholar (GS). It aims to discuss this search engine, which is intended exclusively for searching scholarly documents, and then empirically test its most important functionality. The focus is on an exploratory study which investigates the coverage of scientific serials in GS.Design/methodology/approach – The study is based on queries against different journal lists: international scientific journals from Thomson Scientific (SCI, SSCI, AH), open access journals from the DOAJ list and journals from the German social sciences literature database SOLIS as well as the analysis of result data from GS. All data gathering took place in August 2006.Findings – The study shows deficiencies in the coverage and up‐to‐dateness of the GS index. Furthermore, the study points out which web servers are the most important data providers for this search service and which information sources are highly represented. The paper can show tha...

/pdf/an-exploratory-study-of-google-scholar-29hkdhhaco.pdf

An exploratory study of Google Scholar

This special issue brings together eight papers from experts of communities which often have been perceived as different once: bibliometrics, scientometrics and informetrics on the one side and information retrieval on the other. The idea of this special issue started at the workshop "Combining Bibliometrics and Information Retrieval" held at the 14th International Conference of Scientometrics and Informetrics, Vienna, July 14---19, 2013. Our motivation as guest editors started from the observation that main discourses in both fields are different, that communities are only partly overlapping and from the belief that a knowledge transfer would be profitable for both sides.

/pdf/scientometrics-and-information-retrieval-weak-links-4vbne7zjl5.pdf

Scientometrics and information retrieval: weak-links revitalized

The paper introduces scholarly Information Retrieval (IR) as a further dimension that should be considered in the science modeling debate. The IR use case is seen as a validation model of the adequacy of science models in representing and predicting structure and dynamics in science. Particular conceptualizations of scholarly activity and structures in science are used as value-added search services to improve retrieval quality: a co-word model depicting the cognitive structure of a field (used for query expansion), the Bradford law of information concentration, and a model of co-authorship networks (both used for re-ranking search results). An evaluation of the retrieval quality when science model driven services are used turned out that the models proposed actually provide beneficial effects to retrieval quality. From an IR perspective, the models studied are therefore verified as expressive conceptualizations of central phenomena in science. Thus, it could be shown that the IR perspective can significantly contribute to a better understanding of scholarly structures and activities.

Philipp Mayr

Papers

The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis

The Journal Coverage of Web of Science, Scopus and Dimensions: A Comparative Analysis.

An exploratory study of Google Scholar

Scientometrics and information retrieval: weak-links revitalized

Science models as value-added services for scholarly information systems