Latent DIRICHLET allocation (LDA) based information modelling on BLOCKCHAIN technology: a review of trends and research patterns used in integration

【Author】 Sharma, Chetan; Sharma, Shamneesh; Sakshi

【Source】MULTIMEDIA TOOLS AND APPLICATIONS

【影响因子】2.577

【Abstract】The past decade is known as the era of integrations where multiple technologies had integrated, and new research trends were seen. The security of data and information in the digital world has been a challenge to everyone; Blockchain technology has attracted many researchers in these scenarios. This paper focuses on finding the current trends in Blockchain technology to help the researchers select an area to carry future research. The data related to Blockchain Technologies have been collected from IEEE, Springer, ACM, and other digital databases. Then, the formulated corpus is used for topic modelling, and Latent Dirichlet Allocation is deployed. The outcomes of the Latent Dirichlet Allocation model are then analyzed based on various extracted key terms and key documents found for each topic. All the topic solution has been identified from the bag of words. The extracted topics are thereafter semantically mapped. Thus, based on the analysis of more than 900 papers, the most recent research trends have been discussed in this paper, ultimately focusing on the areas that need more attention from the research community. Also, the meta data analysis has been accomplished, evaluating the year wise and publication source wise research growth. More than 15 research directions are elaborated in this paper, which can direct and guide the researchers to pursuit the research in specific trends and also, find the research gaps in various technologies associated with Blockchain Technology.

【Keywords】Blockchain; Security; Ledger; LDA; Cryptocurrency; Topic modelling

【发表时间】

【收录时间】2022-09-06

【文献类型】综述

【主题类别】

区块链治理-元分析-主题识别