Stock Price Prediction Using Sentiment Analysis:from “Stock Discussion Room” in Naver

Myeongjin Kim, Jihye Ryu, Dongho Cha, Min Kyu Sim

Abstract


The scope of data for understanding or predicting stock prices has been continuously widened from traditional structured format data to unstructured data. This study investigates whether commentary data collected from SNS may affect future stock prices. From “Stock Discussion Room” in Naver, we collect 20 stocks’ commentary data for six months, and test whether this data have prediction power with respect to one-hour ahead price direction and price range. Deep neural network such as LSTM and CNN methods are employed to model the predictive relationship. Among the 20 stocks, we find that future price direction can be predicted with higher than the accuracy of 50% in 13 stocks. Also, the future price range can be predicted with higher than the accuracy of 50% in 16 stocks. This study validate that the investors’ sentiment reflected in SNS community such as Naver’s “Stock Discussion Room” may affect the demand and supply of stocks, thus driving the stock prices.


Full Text:

PDF

References


Hochreiter, S. and Schmidhuber, J., “Long short-term memory,” Neural computation, Vol. 9, No. 8, pp. 1735-1780, 1997.

Hong, S. H., “A study on stock price prediction system based on text mining method using LSTM and stock market news,” Journal of Digital Convergence, Vol. 18, No. 7, pp. 223-228, 2020.

Jeong, J. S., Kim, D. S., and Kim, J. W., “Influence analysis of Internet buzz to corporate performance: Individual stock price prediction using sentiment analysis of online news,” Korea intelligent information Systems Society, Vol. 21, No. 4, pp. 37-51, 2015.

Kang, Y. J. and Jang, W. W., “The Five- Factor Asset Pricing Model: Applications to the Korean Stock Market,” Eurasian Studies, Vol. 13, No. 2, pp. 155-180, 2016.

Kim, D. H., “Asset Pricing Model in Korean Stock Market,” Association of financial engineering, Vol. 13, No. 2, pp. 87-119, 2014.

Kim, D. S., Kim, K. T., and Kim, J. W., “Character-based multi-category sentiment analysis on social media using deep learning algorithms,” Korean Institute Of Industrial Engineers, Vol. 2017, No. 4, pp. 5082-5084, 2017.

Kim, D. Y. and Lee, Y. I., “News based Stock Market Sentiment Lexicon Acquisition Using Word2Vec,” The Korea Journal of BigData, Vol. 3, No. 1, pp. 13-20, 2018.

Kim, D. Y., Park, J. W., and Choi, J. H., “A Comparative Study between Stock Price Prediction Models Using Sentiment Analysis and Machine Learning Based on SNS and News Articles,” Journal of Information Technology Services, Vol. 13, No. 3, pp. 221-233, 2014

Kim, H, G., Kim, S. D., and Kim, H. W., “A Case Study on the Establishment of an Equity Investment Optimization Model based on FinTech: For Institutional Investors,” Korea Knowledge Management Society, Vo. 19, No.1, pp. 97-118, 2018.

Kim, J. Y. and Kim, C. S., “An Analysis on Mediating Effect of Participant Activity in Investment Crowdfunding,” The Journal of Society for e-Business Studies, Vol. 25, No. 1, pp. 65-82, 2020.

Kim, Y. S., Kim, N. G., and Jeong, S. R., “Stock-Index Invest Model Using News Big Data Opinion Mining,” Journal of Intelligence and Information Systems, Vol. 18, No. 2, pp. 143-156, 2012.

Lee, H. J., “Analysis of News Big Data for Deriving Social Issues in Korea,” The Journal of Society for e-Business Studies, Vol. 24, No. 3, pp. 163-182, 2019.

Lee, M. S. and Ahn, H. C., “A Time Series Graph based Convolutional Neural Network Model for Effective Input Variable Pattern Learning: Application to the Prediction of Stock Market,” Korea intelligent information Systems Society, Vol. 24, No. 1, pp. 167-181, 2018.

Park, H. J., Song, M. C., and Sim, K. S., “Sentiment Analysis of Korean Reviews Using CNN-Focusing on Morpheme Embedding,” Korea intelligent information Systems Society, Vol. 24, No. 2, pp. 59-83, 2018.

Seo, I. S., Yeo, S. S., and Kang, H. J., “A Study on the Suggestion of Domestic Stock Market Analysis Scheme using Big Data,” Korean Institute of information technology, Vol. 2014, No. 5, pp. 550-554, 2014.

Son, S. H., Kim, T. H., and Yoon, B. H., “Testing the Linear Asset Pricing Models in the Korean Stock Market,” Korean Journal of Financial Studies, Vol. 38, No. 4, pp. 547-568, 2009.

Song, S. H., Kim, J. H., Kim, H. S., Park, J. S., and Kang, P. S., “Development of Early Warning Model for Financial Firms Using Financial and Text Data: A Case Study on Insolvent Bank Prediction,” Journal of the Korean Institute of Industrial Engineers, Vol. 45, No. 3, pp. 248-259, 2019.

Suh, M. S. and Kim, D. H., “A Study on the Changing Direction of FinTech Service Model based on Big Data,” The e- business studies, Vol. 20, No. 2, pp. 195- 213, 2019.

Yoo, H. S., “What are the core competitiveness and alternative data in the digital age?,” Available at: https://2e.co.kr/news/ articleView.html?idxno=209967, 2019.


Refbacks

  • There are currently no refbacks.