Title:

OS23-4 Exploring Social Media's Role in Predicting Stock Market Trends

Publication: ICAROB2025
Volume: 30
Pages: 623-627
ISSN: 2188-7829
DOI: 10.5954/ICAROB.2025.OS23-4
Author(s): Masatoshi Beppu, Masatomo Ide, Seita Nagashima, Satoshi Ikeda, Amane Takei, Makoto Sakamoto, Tsutomu Ito, Takao Ito
Publication Date: February 13, 2025
Keywords: Sentiment Analysis, Nikkei Stock Average, Social Indicators, Natural Language Processing
Abstract: This study analyzes tweets from the official Twitter accounts of NHK News and Nikkei to incorporate sentiment data into a predictive model for the Nikkei Stock Average. Adding sentiment data improved the R² score from 45.1% to a maximum of 70.5%, indicating the potential of SNS data in forecasting social indicators. However, no strong correlation between sentiment data and stock prices was observed. Challenges include the short data collection period and the difficulty of sentiment analysis in Japanese. Future work should focus on employing more effective methods for extracting sentiment.
PDF File: https://alife-robotics.co.jp/members2025/icarob/data/html/data/OS/OS23/OS23-4.pdf
Copyright: © The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
See for details: https://creativecommons.org/licenses/by-nc/4.0/

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