Measuring News Sentiment of Korea Using Transformer
0
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
We have developed the Korean news sentiment index (NSI) to gauge the economic sentiment of Korea on a daily basis by analyzing news texts gathered from the Internet. Our framework utilizes cutting-edge natural language processing techniques to compute the NSI and examine keywords, offering insights into its fluctuations. We designed a sentiment classifier using transformer neural networks that effectively process extensive news samples to compute the NSI of Korea. We compute the NSI more frequently and immediately than official indices that rely on monthly surveys. Through this, we can identify changes in economic sentiment before official statistics are released. Moreover, the proposed framework offers keyword analysis and sector indices to clarify why economic sentiments fluctuate. Our comprehensive assessments demonstrate that the NSI is a valuable leading index and an essential tool for identifying inflection points in economic sentiment.
Abstract
We have developed the Korean news sentiment index (NSI) to gauge the economic sentiment of Korea on a daily basis by analyzing news texts gathered from the Internet. Our framework utilizes cutting-edge natural language processing techniques to compute the NSI and examine keywords, offering insights into its fluctuations. We designed a sentiment classifier using transformer neural networks that effectively process extensive news samples to compute the NSI of Korea. We compute the NSI more frequently and immediately than official indices that rely on monthly surveys. Through this, we can identify changes in economic sentiment before official statistics are released. Moreover, the proposed framework offers keyword analysis and sector indices to clarify why economic sentiments fluctuate. Our comprehensive assessments demonstrate that the NSI is a valuable leading index and an essential tool for identifying inflection points in economic sentiment.
참고문헌 (33)
- Armah, N. A., "Big Data Analysis: The Next Frontier", Bank of Canada Review, 2013(Summer), pp.32~39 (2013)
- Athey, S., "Machine Learning Methods That Economists Should Know About", Annual Review of Economics, 11(1), pp.685~725 (2019)
- Babii, A., "Machine Learning Time Series Regressions with an Application to Nowcasting", Journal of Business & Economic Statistics, pp.1~23 (2021)
- Baker, S. R., "Measuring Economic Policy Uncertainty", The Quarterly Journal of Economics, 131(4), pp.1593~1636 (2016)
- Barsky, R. B., "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence", American Economic Review, 102(4), pp.1343~1377 (2012)
- Bennani, H., "The(home)Bias of European Central Bankers : New Evidence Based on Speeches", Applied Economics, 49(11), pp.1114~1131 (2017)
- Business News and Business Cycles, "Bybee, L.", National Bureau of Economic Research, ~ (2021)
- "Keras" (2015)[URL]
- Gentzkow, M., "Text as Data", Journal of Economic Literature, 57(3), pp.535~574 (2019)
- Heaton, J., "Introduction to Neural Networks with Java" (2008), Heaton Research, Inc
- News-based Sentiment Indicators, "Huang, C.", International Monetary Fund, ~ (2019)
- "2020"
- "2019", 2019(2)
- "2021", 2021(1)
- Larsen, V. H., "News-driven Inflation Expectations and Information Rigidities", Journal of Monetary Economics, 117, pp.507~520 (2021)
- LeCun, Y., "Deep Learning", Nature, 521(7553), pp.436~444 (2015)
- Lee, Y. J., "Deciphering Monetary Policy Board Minutes with Text Mining : The Case of South Korea", The Korean Economic Review, 35(2), pp.471~511 (2019)
- Measuring Monetary Policy Surprises using Text Mining: The Case of Korea, "Lee, Y. J.", Bank of Korea, ~, pp.WP, 11 (2019)
- Loughran, T., "When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-ks", The Journal of Finance, 66(1), pp.35~65 (2011)
- "2019", 11(4)
- Start Spreading the News : News Sentiment and Economic Activity in Australia, "Nguyen, K.", Reserve Bank of Australia, 33~ (2020)
- "Open Korean Text (okt)" (2014)[URL]
- Seki, K., "News-based Business Sentiment and its Properties as an Economic Index", Information Processing & Management, 59(2), pp.102795~ (2022)
- "2022", 2022(1)
- Shapiro, A. H., "Measuring News Sentiment", Journal of Econometrics (2020)
- Nowcasting using News Topics. Big Data Versus Big Bank, "Thorsrud, L. A.", Centre for Applied Macro and Petroleum Economics (CAMP), BI Norwegian Business School, ~, pp.Working Papers, 2016(6) (2016)
- Thorsrud, L. A., "Words are the New Numbers : A Newsy Coincident Index of the Business Cycle", Journal of Business & Economic Statistics, 38(2), pp.393~409 (2020)
- van Aarle, B., "Economic Sentiment Shocks and Fluctuations in Economic Activity in the Euro Area and the usa", Intereconomics, 47(1), pp.44~51 (2012)
- Vaswani, A., "Attention is All You Need", Advances in Neural Information Processing Systems, 30 (2017)
- Webster, J. J., "Tokenization as the Initial Phase in nlp", COLING 1992: The 14th International Conference on Computational Linguistics, 4 (1992)
- "2017", 2017(4)