Text Data Pre-Processing for Time-series Modelling

被引：0

作者：

Pomenkova, Jitka ^{[1
]}

Korab, Petr ^{[2
]}

Strba, David ^{[3
]}

机构：

[1] Brno Univ Technol, Dept Radio Elect, Brno, Czech Republic

[2] Zeppelin Univ, Lentiamo, Czech Republic

[3] Lentiamo, Prague, Czech Republic

来源：

2023 33RD INTERNATIONAL CONFERENCE RADIOELEKTRONIKA, RADIOELEKTRONIKA | 2023年

关键词：

text mining; natural language processing; time-series modeling; data pre-processing; PRICES;

D O I：

10.1109/RADIOELEKTRONIKA57919.2023.10109034

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The paper proposes an algorithm of text data representation for time-series econometric modeling. We link two areas in empirical econometrics, text mining and time-series modeling, and provide a multi-step methodology for processing qualitative text data for quantitative time-series models. We also present an empirical example of text data processing of research article meta-data in economics and show its applicability to sentiment analysis using annual data from 1933 - 2015

引用

页数：6

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