Sentiment Analysis for Multilingual Corpora

被引：0

作者：

Galeshchuk, Svitlana ^{[1
]}

Qiu, Ju ^{[2
]}

Jourdan, Julien ^{[1
]}

机构：

[1] PSL Res Univ, Governance Analyt, Univ Paris Dauphine, Pl Marechal Lattre Tassigny, F-75016 Paris, France

[2] PSL Res Univ, Univ Paris Dauphine, Pl Marechal Lattre Tassigny, F-75016 Paris, France

来源：

7TH WORKSHOP ON BALTO-SLAVIC NATURAL LANGUAGE PROCESSING (BSNLP'2019) | 2019年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper presents a generic approach to the supervised sentiment analysis of social media content in foreign languages. The method proposes translating documents from the original language to English with Google's Neural Translation Model. The resulted texts are then converted to vectors by averaging the vectorial representation of words derived from a pretrained Word2Vec English model. Testing the approach with several machine learning methods on Polish, Slovenian and Croatian Twitter corpora returns up to 86 % of classification accuracy on the out-of-sample data.

引用

页码：120 / 125

页数：6

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