A review of machine learning for big data analytics: bibliometric approach

El-Alfy, El-Sayed M.; Mohammed, Salahadin

doi:10.1080/09537325.2020.1732912

Cited by 27 publications

(11 citation statements)

References 52 publications

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“…Computational and programming literacy was the most prevalent theme, with 18 occurrences. This reflects the status quo because Big Data analytics is generally characterized with reference to programming and machine learning, which are sub-fields of computer science (El-Alfy & Mohammed, 2020). In contrast, the meaning and definition of Big Data and critical analysis and effective communication skills, both had the lowest frequency (2), albeit these generally relate to the data context, which is fundamental to producing and presenting meaningful and actionable results.…”

Section: Resultsmentioning

confidence: 99%

Perspectives on Curricular Priorities for Big Data Analytics: A Qualitative Study of Educators and Practitioners

Hassad¹

2022

Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference

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Big Data is a universal concept that has become a metaphor for innovation and discovery; however, deriving this benefit requires going beyond traditional tools and expertise. The aim of this qualitative study (N=38) was to explore perspectives on curricular priorities for Big Data analytics from educators and practitioners. Nine themes were derived: computational and programming literacy, integrated and multidisciplinary curriculum, data quality and methodological standards, collaboration and domain-specific expertise, statistical literacy, basic statistics (probability and inference), ethico-legal considerations, critical analysis and effective communication skills, and meaning and definition of Big Data. Additionally, reflective learning was identified as an overarching theme, which can serve as a unifying pedagogical approach. These results provide a framework that appears to have content validity for informing curricular reform and development.

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Section: Resultsmentioning

confidence: 99%

Perspectives on Curricular Priorities for Big Data Analytics: A Qualitative Study of Educators and Practitioners

Hassad¹

2022

Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference

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“…The United States and the Peoples' Republic of China account for a signi cant volume. Both of these countries have been identi ed previously as power houses for publishing research in the eld of cancer and others (34)(35)(36)(37)(38). Despite their high overall output, correction for population has highlighted research hotspots such as Luxembourg, Switzerland and Singapore who lead the world in publications per capita but also have the highest average citations among all countries.…”

Section: Discussionmentioning

confidence: 99%

The Future of Mesenchymal Stromal Cells in cancer – A Bibliometric Analysis

O'Connor¹,

Barkley²,

Kerin³

2020

Preprint

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BackgroundMesenchymal stromal/stem cells have garnered much interest in the field of cancer biology. Bibliometric analysis of a scientific field has the potential to reveal insights pertaining to the maturity of the field, the hotspot sources of publication and temporal shifts in research subcategories within the field. Despite the benefits of such an analysis, one has not been conducted to date.MethodsThe Web of Science™database and VOSviewer software were used to analyse publication and citation data for all publications relating to Mesenchymal Stromal/Stem Cells in oncology. Contributions to the literature were also identified by country, journal and cancer type. Keyword analysis identified trends in developing research categories.Results9927 published articles were analysed. The current publication rate fits an exponential trend(r2 = 0.97). The U.S. and the People’s Republic of China have the highest overall publications but when corrected for population and citations per article, the most successful countries are Singapore, Luxembourg and Switzerland. In the past 15 years 74% of articles have been in cancer specific journals. Breast cancer publications account for 42% of common cancer articles. Most articles were published in journals that had a basic science focus (44%). Keyword analysis resulted in 3 distinct clusters aligned with 1. Characterisation and nomenclature, 2.Clinical and 3.Molecular function. The most recent publications favour topics on Molecular function. ConclusionsResearch on Mesenchymal Stromal/Stem Cells in oncology is experiencing exponential growth. There is widespread acceptance of basic science research on MSCs in cancer specific journals and a niche for more translational and clinically focused studies.

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“…A typical work in this line of research was a bibliometric review of computational linguistics from a general perspective (Radev, 2016). Other works included studies that investigated the landscape of specific research areas such as topic modeling (Li & Lei, 2019), big data (Raban & Gordon, 2020), digital library (Ahmad et al, 2018), machine learning (Elalfy & Mohammed 2020; Santos et al, 2019), Internet of Things (Erfanmanesh & Abrizah, 2018), decision making (Zyoud & Fuchs-Hanusch, 2017a), and environmental studies (Zhang et al, 2020; Zheng et al, 2017; Zyoud & Fuchs-Hanusch, 2017b, 2020; Zyoud & Zyoud, 2021).…”

Section: Introductionmentioning

confidence: 99%

The Research Trends of Text Classification Studies (2000–2020): A Bibliometric Analysis

Zhu

Lei

2022

SAGE Open

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Text Classification (TC) is the process of assigning several different categories to a set of texts. This study aims to evaluate the state of the arts of TC studies. Firstly, TC-related publications indexed in Web of Science were selected as data. In total, 3,121 TC-related publications were published in 760 journals between 2000 and 2020. Then, the bibliographic information was mined to identify the publication trends, important contributors, publication venues, and involved disciplines. Besides, a thematic analysis was performed to extract topics with increasing/decreasing popularity. The findings showed that TC has become a fast-growing interdisciplinary area, and that emerging research powers such as China are playing increasingly important roles in TC research. Moreover, the thematic analysis showed increased interest in topics concerning advanced classification algorithms, performance evaluation methods, and the practical applications of TC. This study will help researchers recognize the recent trends in the area.

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A review of machine learning for big data analytics: bibliometric approach

Cited by 27 publications

References 52 publications

Perspectives on Curricular Priorities for Big Data Analytics: A Qualitative Study of Educators and Practitioners

Perspectives on Curricular Priorities for Big Data Analytics: A Qualitative Study of Educators and Practitioners

The Future of Mesenchymal Stromal Cells in cancer – A Bibliometric Analysis

The Research Trends of Text Classification Studies (2000–2020): A Bibliometric Analysis

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