Text Mining-based Economic Activity Estimation

Ksenia Yakovleva
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引用次数: 5

Abstract

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.
基于文本挖掘的经济活动估计
本文概述了构建俄罗斯经济活动高频指标的方法。来自互联网资源的新闻故事被用作数据源。新闻数据使用文本挖掘和机器学习方法进行分析,尽管这些方法发展相对较晚,但在科学研究(包括经济研究)中迅速得到广泛应用。这是因为新闻不仅是信息的主要来源,而且是衡量记者和调查对象对当前形势的看法并将其转化为定量数据的一种方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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