• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.

• The Journal of Industrial Distribution & Business
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• v.13 no.6
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• pp.1-7
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• 2022

Purpose: This study aims to investigate an overview of the reputation of e-commerce from 2001-2021. Research design, data and methodology: This study uses a bibliometrics technique involving published results from the Scopus database. Keyword tracking uses the terms e-commerce + reputation. The data collected meets the criteria for the type of journal publication. Data was collected using the Publish or Perish (PoP) program and exported into VOSviewer. Bibliometrics examines certain fields of science based on several components such as author and co-author, citation and co-citation, keywords related to theme mapping, origin, and source of publication. Data was collected using the Publish or Perish (PoP) program and exported into VOSviewer. Results: The results show the total citations from 118 papers are 1429, with citations per paper of 12.11 and citations per year of 68.05. The trend of publications from 2001-2021 shows the dynamics of increasing or decreasing, but this trend is still developing. Conclusions: This paper also presents articles that have contributed greatly to the study of e-commerce reputation, the most productive authors, and clustered themes regarding e-commerce reputation. Reputation is an important area of e-commerce research. Reputation is also essential factors for e-commerce in facing business competition and needs to be a consideration for digital business practitioners.