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作 者:Xian Zhuo Felix Irresberger Denefa Bostandzic
机构地区:[1]Manchot Graduate School,Heinrich Heine University Düsseldorf,Universitätsstr.1,40225,Düsseldorf,Germany [2]Durham University Business School,Durham University,Mill Hill Lane,DH13LB,Durham,Germany [3]Department of Management and Entrepreneurship,Witten/Herdecke University,Alfred-Herrhausen-Str.50,58448,Witten,Germany
出 处:《Financial Innovation》2024年第1期2304-2338,共35页金融创新(英文)
基 金:supported by the Manchot Graduate School“Competitiveness of Young Enterprises”at the Heinrich-Heine-University of Düsseldorf.Funding was provided by the Jürgen Manchot Stiftung.
摘 要:This paper provides a systematic literature review of text analysis methodologies used in blockchain-related research to comprehend and synthesize existing studies across disciplines and define future research directions.We summarize the research scope,text data,and methodologies of 124 papers and identify the two most common combinations of these dimensions:(1)papers that focus on specific cryptocurrencies tend to apply sentiment analysis to instant user-generated content or news articles to discover the correlations between public opinion and market behavior,and(2)studies that examine the broad concept of blockchain with text data from documents published by companies tend to apply topic modeling techniques to explore classifications and trends in blockchain development.We discover five major research topics in the academic literature:relationship discovery,cryptocurrency performance prediction,classification and trend,crime and regulation,and perception of blockchain.Based on these findings,we highlight three potential research directions for researchers to select topics and implement suitable methodologies for text analysis.
关 键 词:Blockchain Text analysis Systematic literature review Machine learning algorithm Topic modeling Sentiment analysis
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