Google Scholar, Microsoft Academic and Worfram Alpha

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Table of Contents

Introduction
Method
Google Scholar
Microsoft Academic
Wolfram Alpha
Conclusion
Reference List

Introduction

Academic search engines and bibliographic databases (ASEBDs) are regarded as the primary platform for accessing up-to-date scientific publications. Scholars often utilize ASEBDs to provide a lens via which they could perform analyses (Apuke and Iyendo, 2018; Croft, Metzler and Strohman, 2015). The rise of the Internet in the late 1990s led to the emergence of ASEBDs which replaced conventional offline systems (Dagienė and Danutė, 2016). Nonetheless, in the early 2000s, technological innovations resulted in the development of sizeable crawler-based search engines, such as Microsoft Academic and Google Scholar (Dagienė and Danutė, 2016; Fagan, 2017). Google Scholar established itself as the dominant go-to information source in academia, and it seemed incomparable based on the efficiency and adequate provision of online scholarly documents (Gusenbauer, 2019; Mingers and Meyer, 2017). Nevertheless, after halting its service, Microsoft Academic relaunched its academic search engine in 2017 to rival the former (Harzing and Alakangas, 2017b).

In addition to Microsoft Academic and Google Scholar, there are other information sources, such as Wolfram Alpha, that try to convince academicians of the validity of the information that they constitute. Unlike the former search engines, Wolfram Alpha is a computational knowledge engine that generates searches through performing computations from the Wolfram database instead of the web (Wolfram Alpha, 2020a). Even though people have access to various platforms, it is often unclear which system best suits their needs. There are different benchmarks available for assessing the quality of ASEBDs, for instance, accessibility, industry value, reliability, currency, and strengths, and weaknesses. This study concentrates on comparing the five criteria concerning Google Scholar, Microsoft Academic, and Wolfram Alpha.

Method

Searches were performed in Google Scholar, Microsoft Academic, and Wolfram Alpha to approximate a user’s approach to the same topic, “plane turbine engine”. The search results were evaluated for the information they provided regarding the turbine engine and engineering in general. For every search, the search results were examined to determine various characteristics, including accessibility, industry value, reliability, currency, strengths, and weaknesses. In addition, other searches were narrowed by date to generate sets of reasonable size, therefore, allowing for the comparison of unique items retrieved by every service system.

Google Scholar

Accessibility

Google Scholar is a free-to-access search engine that provides end-users access to comprehensive and multidisciplinary content. The site is characterized to have a convenient and straightforward interface that facilitates smooth and quick searching, leading to its usability. The search engine contained a mixture of full-text and subscription plan articles. Although not all documents were available in full-text form, Google Scholar had a significant resource of 438,000 documents.

Accessibility

Industry Value

Google Scholar is an excellent engine for individual assessment as it draws from a wide array of documents, whereby some sources go beyond scientific publishing channels (Jamali and Majid, 2015; Martín-Martín, Orduna-Malea and Delgado, 2018). These types of sources have a considerable academic impact on the Web. Moreover, current articles, which are less than five years old, comprehensively covered the searched topic. For instance, on the first page, none of the sources had the keywords “plane turbine engine” highlighted in their titles. Therefore, this diminishes the relevance of the search engine. In summation, Google Scholar is relatively suitable for researching engineering disciplines (Cole et al., 2018).

Industry Value

Reliability

Google Scholar provides a simple and efficient method of accessing abstracts, books, peer-reviewed papers, and articles from professional societies, academic publishers’ sites, and universities. However, since the system comprises various documents that have not been peer-reviewed, its credibility as a reliable source for scholarly articles wanes (Halevi, Moed and Bar-Ilan, 2017; Harzing and Alakangas, 2016; Martín-Martín et al., 2017).

Currency

It contains documents created and published from the 1900s to the 2000s. Therefore, to facilitate the narrowing down on up-to-date information, the engine has a filter option that allows the generation of documents published within the specified date. For instance, adjusting the date ranges from 2015 – 2020 yields a total of 17,800 documents.

Currency

Strength and Weakness

One strength of Google Scholar is its simple user interface, in which the leading search engine interface comprises a query box. Furthermore, the site provides access to more grey literature since it retrieves institutional repositories, preprint archives, and conference proceedings, in addition to the journals. This is also mirrored in Bonato (2016) and Haddaway et al. (2015). Lastly, the engine offers a “cited by” feature under each source.

Strength and Weakness

Although it has numerous strengths, the engine also has its flaws. The system’s weaknesses in its search interface include the absence of reliable advanced search functions, inability to search controlled vocabulary, or the lack of authority for author or journal names. Some of the unique items retrieved were off-topic. These are probably attributed to “false hits” associated with Google Scholar’s full-text searching accompanied by the lack of controlled vocabulary. For instance, the search was to locate articles on the topic of “plane turbine engine”. The search engine retrieved 438,000 documents where the searched words appeared in the full-text, although lacking in the main topic.