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This scientific paper aims to explore the published science on the use of artificial neural networks for text mining in the specific field of management. For this purpose, a specific query is defined through the Scopus database and articles published on the topic from the year 2000 to 2023 are downloaded. After gathering, cleaning, processing, analysing and visualising the data obtained from the documents using the VantagePoint and Gephi tools, research trends are obtained as a result. It is concluded that it is a field that is growing in recent years and that the main country in terms of number of publications is China. In addition, we identify the types of neural networks that are used, the applications that are given to them and the topics in which they are used. The conclusion is that convolutional neural networks predominate as a type of network, sentiment analysis as an application and social media as data source.

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Artificial Neural Networks for Text Mining in Management Field – Scientific Research Direction

  • 会议论文

  • 发表日期：

    2025年

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  • Maite Jaca-Madariaga,
  • Enara Zarrabeitia-Bilbao,
  • Rosa María Rio-Belver,
  • Izaskun Alvarez-Meaza

摘要

This scientific paper aims to explore the published science on the use of artificial neural networks for text mining in the specific field of management. For this purpose, a specific query is defined through the Scopus database and articles published on the topic from the year 2000 to 2023 are downloaded. After gathering, cleaning, processing, analysing and visualising the data obtained from the documents using the VantagePoint and Gephi tools, research trends are obtained as a result. It is concluded that it is a field that is growing in recent years and that the main country in terms of number of publications is China. In addition, we identify the types of neural networks that are used, the applications that are given to them and the topics in which they are used. The conclusion is that convolutional neural networks predominate as a type of network, sentiment analysis as an application and social media as data source.