Sentiment Analysis on English Financial News

被引：6

作者：

Eremeeva, Guzel Rinatovna ^{[1
]}

Martynova, Ekaterina Vladimirovna ^{[1
]}

Khakimova, Amina Aidarovna ^{[1
]}

Ilikova, Liliya Ernstovna ^{[1
]}

机构：

[1] Kazan Fed Univ, Kazan, Russia

来源：

JOURNAL OF RESEARCH IN APPLIED LINGUISTICS | 2019年 / 10卷

关键词：

Linguistics; Text; Sentiment Analysis; Polarity Detection;

D O I：

10.22055/RALS.2019.15102

中图分类号：

H0 [语言学];

学科分类号：

030303 ; 0501 ; 050102 ;

摘要：

This article is devoted to comparison of various approaches towards sentiment analysis (polarity classification) of the English financial news. The purpose of the work is to check, weather higher quality English texts would have higher classification quality and the links between quality of polarity classification and the architectures of the chosen systems. The approaches, presented on SemEval-2017 competition in the appropriate category of tasks, are taken as the basis. A specially collected dataset is used as the source of English financial news. In the end, a conclusion is made about the relationship between the quality of the source of English financial news and the quality of the news data sentiment analysis, made by the compared systems.

引用

页码：574 / 582

页数：9

共 12 条

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