News Articles Evaluation Analysis in Automotive Industry Using GPT-2 and Co-occurrence Network

Yoshihiro Nishi, Aiko Suge, Hiroshi Takahashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

News articles have great impacts on asset prices in the financial markets. Many attempts have been reported to ascertain how news influences stock prices. Stock price fluctuations of highly influential companies can have a major impact on the economy as a whole. In particular, the automobile industry is a colossal industry that leads the Japanese industry. However, the limitations in the number of available data sets usually become the hurdle for the model accuracy. In this study, we constructed a news evaluation model utilizing GPT-2. A news evaluation model is a model that evaluates news articles distributed to financial markets based on price fluctuation rates and predicts fluctuations in stock prices. We have added news articles generated by GPT-2 as data for analysis. Besides, we used a co-occurrence network analysis to review the overview of the news articles. News articles were classified through Long Short-Term Memory (LSTM). The results showed that the accuracy of the news evaluation model improved by generating news articles using a language generation model through GPT-2. More detailed analyses are planned for the future.

Original languageEnglish
Title of host publicationNew Frontiers in Artificial Intelligence - JSAI-isAI International Workshops, JURISIN, AI-Biz, LENLS, Kansei-AI, 2019, Revised Selected Papers
EditorsMaki Sakamoto, Naoaki Okazaki, Koji Mineshima, Ken Satoh
PublisherSpringer Science and Business Media Deutschland GmbH
Pages103-114
Number of pages12
ISBN (Print)9783030587895
DOIs
Publication statusPublished - 2020
Event11th JSAI International Symposium on Artificial Intelligence, JSAI-isAI 2019 - Yokohama, Japan
Duration: 2019 Nov 102019 Nov 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12331 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th JSAI International Symposium on Artificial Intelligence, JSAI-isAI 2019
CountryJapan
CityYokohama
Period19/11/1019/11/12

Keywords

  • Co-occurrence network
  • Deep learning
  • Financial markets
  • GPT-2
  • Language generation
  • LSTM

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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