Open AccessAUTOMATIC EMOTION IDENTIFICATION IN RUSSIAN TEXT MESSAGES
Author(s) -
Aleksandr Babii,
Marina Kazyulina
Publication year - 2020
Publication title -
kompʹûternaâ lingvistika i intellektualʹnye tehnologii
Language(s) - English
Resource type - Conference proceedings
ISSN - 2075-7182
DOI - 10.28995/2075-7182-2020-19-1002-1010
Subject(s) - computer science , emotive , relevance (law) , natural language processing , identification (biology) , classifier (uml) , artificial intelligence , sentiment analysis , philosophy , botany , epistemology , political science , law , biology
Automatic emotive text analysis has demonstrated its relevance in recent years. In this paper, we address the issue of identification emotions in the text of informal internet-discourse of the Russian language. We consider text messages collected from Telegram and VK. Due to difficulty of such advanced form of sentiment analysis, this paper proposes an integrated approach to combining linguistic methods and machine learning. As a result, an automatic classifier of text messages on expressed emotions is designed. On testing, our model is estimated to provide near-human performance.