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Study on Business Strategy Quantification Using Topic Modeling and Word Embedding: Focusing on 'Virtual Reality' and 'Augmented Reality'

机译:使用主题建模和单词嵌入的业务战略量化研究:专注于“虚拟现实”和“增强现实”

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This study analyzed articles related to "Virtual Reality" and "Augmented Reality," the main elements of the Fourth Industrial Revolution, and reviewed the views that the media has by using text mining techniques. For this, 14,443 news articles on "Virtual Reality" and "Augment Reality" from 2011 to 2020 were collected from the BigKinds of Korea Press Foundation. For the analysis of collected datasets, the LDA algorithm-based topical modeling techniques implemented in Python3 languages were used. The number of topics suitable for the collected dataset using coherence was determined to be 14. The calculated topic was given the title of the topic through expert survey, and word vector was created using Word2vec, one of the word-embedding techniques. This word vector was then used to quantify the analyzed topic. Through this, quantitative expressions of strategic perspectives were made and changes in topics around the year 2016 were visualized when the issue of the "fourth industrial revolution" began to be discussed.
机译:本研究分析了与“虚拟现实”和“增强现实”相关的文章,第四个工业革命的主要要素,并审查了媒体使用文本挖掘技术的观点。为此,从2011年到2020年从2011年到2020年的“虚拟现实”和“增强现实”的14,443篇关于韩国新闻基金会的新闻文章。为了分析收集的数据集,使用了在Python3语言中实现的基于LDA算法的主题局部建模技术。基于使用一致性的收集数据集的主题数量是14.计算出通过专家调查给出了主题的标题,并使用Word2VEC创建了一个单词嵌入技术的单词矢量。然后使用该字向量来量化分析的主题。通过这一点,当“第四次工业革命”开始讨论时,对战略观点的定量表达进行了制定和2016年左右的主题变化。

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