Market Analysis of Key Manufacturing Segments Using News Data

Sung Wook Hong () and Seong-hwan Min ()
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Sung Wook Hong: Korea Institute for Industrial Economics and Trade, Postal: Sejong National Research Complex, Korea Institute for Industrial Economics and Trade, 370 Sicheong Dae-ro C-dong 8-12F 30147, Republic of Korea, http://www.kiet.re.kr
Seong-hwan Min: Korea Institute for Industrial Economics and Trade, Postal: Sejong National Research Complex, Korea Institute for Industrial Economics and Trade, 370 Sicheong Dae-ro C-dong 8-12F 30147, Republic of Korea, http://www.kiet.re.kr

No 21/8, Research Papers from Korea Institute for Industrial Economics and Trade

Abstract: This paper examines the use and viability of unstructured data in forecasting the real economy in order to quickly understand the current situation and trends in the real economy in light of growing uncertainty both domestically and externally. To extract an index utilizing news data, the methodology of Thorsrud (2016) was used to develop two approaches. The first approach involves conducting topic analysis to extract topics and then employing sentiment analysis for each topic and calculating a simple index. The second approach involves creating a comprehensive score by combining the sentiment score and topic score to create a sort of composite index. To prove the utility of news data-based indices, the total population was set to match the number of topics that had the maximum number of word groups of all of the news data from the six segments of the manufacturing industry for the given period. That number was then reduced based on topics that met a certain standard, and the correlation between the extracted indices and real industry indices (such as an increase in the segment-based manufacturing index) was examined. In conclusion, the numbers calculated by analyzing the news for each segment of the manufacturing industry showed a similar trend to that of the real economy, showing that data extracted in a quantitative manner from unstructured data such as news articles prove to be significantly useful in understanding trends in the real economy.

Keywords: real economy; forecasting; economic forecasting; news data; topic analysis; sentiment analysis; manufacturing; unstructured data; Korea (search for similar items in EconPapers)
JEL-codes: C50 C53 C59 C82 C83 C89 E37 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2021-05-21
New Economics Papers: this item is included in nep-big and nep-mac
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