International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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A Study on Research Trend Analysis and Topic Class Prediction of Digital Transformation using Text Mining

  • Received : 2019.05.25
  • Accepted : 2019.06.10
  • Published : 2019.06.30
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Abstract

In the era of the Fourth Industrial Revolution, digital transformation, which means changes in all industrial structures, politics, economics and society as well as IT technology, is an important issue. It is difficult to know which research topic is being studied because digital transformation is being studied in various fields. Convergence research is possible because a research topic is studied in various fields such as computer science area and Decision science area. However, it is difficult to know the specific research status of the research topic. In this study, eight research topics were derived using the topic modeling technique of text mining for abstract of academic literature and the trend of each topic was analyzed. We also proposed to create a Topic-Word Proportions Table in the LDA based Topic modeling process to predict the topic of new literature. The results of this study are expected to contribute to advanced convergence research on topic of digital transformation. It is expected that the literature related to each research topic will be grasped and contribute to the design of a new convergence research.

Keywords

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Figure 1. LDA graphical model for Topic modeling [12]

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Figure 2. Research Framework

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Figure 3. Data collection results

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Figure 4. Time trends of 8 topics from 2009 to 2018.

Table 1. Extracted topics for Digital Transformation

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Table 2. Topic-word Proportions Table

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