Predicting Trends and Research Patterns of Smart Cities: A Semi-Automatic Review Using Latent Dirichlet Allocation (LDA)
Abstrak
Smart cities are a current worldwide topic requiring much scientific investigation. This research instigates the necessity of an organized review to a heedful insight of the research trends and patterns prevailing in this domain. The string is formulated to extract the corpus from Scopus largest database of publications. The corpus of 8320 articles published from 2010 to 2022 is processed using Latent Dirichlet Allocation. Two, five, and ten topics have been extracted to provide the recent trends for IoT in smart cities. There has been an increased recognition that more attention needs to be paid to the area of smart cities so a complete overview of the topic of smart cities research, including the most prominent nations (institutions, sources, and authors) and noteworthy research directions has been presented in this paper. The scientific collaboration across countries (regions), organizations, and authors has also been widely discussed. A detailed and comprehensive overview and visualization of the trends and research patterns used to integrate the Internet of Things in Smart Cities. This data based experimental study signifies a roadmap of the research trends in Smart Cities by implementing topic modeling technique that has never been used in this domain. Based upon the topic modeling using LDA, authors have formulated three research questions and answered those question based on the in-depth research. At the end this study concludes the areas suggested are at the growing phase and need more insight for their growth.
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Daftar Referensi
3 referensiLatent DIRICHLET allocation (LDA) based information modelling on BLOCKCHAIN technology: a review of trends and research patterns used in integration
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20 Agustus 2022
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.
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Qingjun Wang Zhihan Lv + 2 lainnya
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