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.

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区块链研究中如何分析文本？系统的文献综述

本文对区块链相关研究中使用的文本分析方法进行了系统的文献综述，以理解和综合跨学科的现有研究并确定未来的研究方向。我们总结了 124 篇论文的研究范围、文本数据和方法，并确定了这些维度的两种最常见的组合：（1）专注于特定加密货币的论文倾向于将情绪分析应用于即时用户生成的内容或新闻文章以发现公众舆论与市场行为之间的相关性；（2）利用公司发布的文档中的文本数据检验区块链的广泛概念的研究倾向于应用主题建模技术来探索区块链发展的分类和趋势。我们在学术文献中发现了五个主要研究主题：关系发现、加密货币性能预测、分类和趋势、犯罪和监管以及区块链感知。基于这些发现，我们强调了三个潜在的研究方向，供研究人员选择主题并实施合适的文本分析方法。