Text Mining-based Economic Activity Estimation
Ksenia Yakovleva ()
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Ksenia Yakovleva: Bank of Russia
Russian Journal of Money and Finance, 2018, vol. 77, issue 4, 26-41
This paper outlines a methodology for constructing a high-frequency indicator of economic activity in Russia. News stories from internet resources are used as data sources. News data is analyzed using text mining and machine learning methods, which, although developed relatively recently, have quickly found wide application in scientific research, including economic studies. This is because news is not only a key source of information but a way to gauge the sentiment of journalists and survey respondents about the current situation and convert it into quantitative data.
Keywords: economic activity estimates; nowcasting; text mining; machine learning; Big Data; data mining; topic modelling; sentiment analysis (search for similar items in EconPapers)
JEL-codes: E37 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:bkr:journl:v:77:y:2018:i:4:p:26-41
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