A bibliometric analysis of bitcoin scientific production

Merediz-Solà, Ignasi; Bariviera, Aurelio F.

doi:10.1016/j.ribaf.2019.06.008

Cited by 153 publications

(72 citation statements)

References 79 publications

(75 reference statements)

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“…It also involves descriptive linguistics (Gleason, 1961), the development of thesauri, the evaluation of reader usage, and the analysis of associated keywords. All these bibliometrics patterns are used to identify research clusters, emerging topics, and leading scholars in bitcoin literature by analyzing 1,162 papers indexed in Web of Science (Merediz‐Solà & Bariviera, 2019).…”

Section: Literature‐based Analysismentioning

confidence: 99%

Scholarly data mining: A systematic review of its applications

Dridi

Gaber

Azad

et al. 2020

WIREs Data Min & Knowl

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During the last few decades, the widespread growth of scholarly networks and digital libraries has resulted in an explosion of publicly available scholarly data in various forms such as authors, papers, citations, conferences, and journals. This has created interest in the domain of big scholarly data analysis that analyses worldwide dissemination of scientific findings from different perspectives. Although the study of big scholarly data is relatively new, some studies have emerged on how to investigate scholarly data usage in different disciplines. These studies motivate investigating the scholarly data generated via academic technologies such as scholarly networks and digital libraries for building scalable approaches for retrieving, recommending, and analyzing the scholarly content. We have analyzed these studies following a systematic methodology, classifying them into different applications based on literature features and highlighting the machine learning techniques used for this purpose. We also discuss open challenges that remain unsolved to foster future research in the field of scholarly data mining. This article is categorized under: Algorithmic Development > Text Mining Application Areas > Science and Technology

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Section: Literature‐based Analysismentioning

confidence: 99%

Scholarly data mining: A systematic review of its applications

Dridi

Gaber

Azad

et al. 2020

WIREs Data Min & Knowl

View full text Add to dashboard Cite

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“…Merediz-Sola & Bariviera (2019) analysed metadata of all the papers indexed in the Web of Science Core Collection that contained bitcoin as topic for the period 2012-January 2019, in a total of 1162 documents.…”

Section: A Study Design;mentioning

confidence: 99%

Bitcoin in the Scientific Literature – A Bibliometric Study

Ramona

Cristina

Sava

2019

Studies in Business and Economics

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Since 2012, there has been growing interest in bitcoin scientific research from different fields, including computer science and engineering, economics, business and finance, law and regulatory. The purpose of this paper is to evaluate bitcoin literature based on the structures and networks of science, as a first step in the research of this new phenomenon. Analysing the growing scientific literature on bitcoin published between 2012 and 2019, we provided useful insights on academic research in this field regarding publication year, type and category, authors, journals and citations. The source of the 887 documents which support the study was Web of Science Core Collection. Using VOSviewer software we have designed bibliometric maps based on text and bibliographic data. Our study provides a knowledge area map that identifies and evaluates the links between authors and countries distribution, the conceptual structure of the field, the structure and connections of most cited papers and journals. Resuming our findings, we note a concentration of the interest on some keywords (bitcoin, cryptocurrency, blockchain) and on some influential authors (with more than 100 citations per article). As a pure expression of digital economy, the research on bitcoin as an economic concept counts only 33.5% from the total contributions in the field.

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“…The two closest papers to ours are Corbet et al . (2019) and Merediz‐Solà and Bariviera (2019). The first one produces a systematic review of 52 quantitative investigations of cryptocurrency markets.…”

Section: Introductionmentioning

confidence: 97%

Where Do We Stand in Cryptocurrencies Economic Research? A Survey Based on Hybrid Analysis

Bariviera

Merediz-Solà

2021

Journal of Economic Surveys

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This survey develops a dual analysis, consisting, first, in a bibliometric examination and, second, in a close literature review of all the scientific production around cryptocurrencies conducted in economics so far. The aim of this paper is twofold. On the one hand, proposes a methodological hybrid approach to perform comprehensive literature reviews. On the other hand, we provide an updated state of the art in cryptocurrency economic literature. Our methodology emerges as relevant when the topic comprises a large number of papers, which make unrealistic to perform a detailed reading of all the papers. This dual perspective offers a full landscape of cryptocurrency economic research. First, by means of the distant reading provided by machine learning bibliometric techniques, we are able to identify main topics, journals, key authors, and other macro aggregates. Second, based on the information provided by the previous stage, the traditional literature review provides a closer look at methodologies, data sources, and other details of the papers. In this way, we offer a classification and analysis of the mounting research produced in a relative short time span.

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A bibliometric analysis of bitcoin scientific production

Cited by 153 publications

References 79 publications

Scholarly data mining: A systematic review of its applications

Scholarly data mining: A systematic review of its applications

Bitcoin in the Scientific Literature – A Bibliometric Study

Where Do We Stand in Cryptocurrencies Economic Research? A Survey Based on Hybrid Analysis

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