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Title: Automatic Recognition of Emotions in Text
Authors: Novakov, Todor
Koychev, Ivan
Keywords: Machine learning
Multi-label classification
Emotion classification
Issue Date: 1-Jun-2018
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences, Association for the Development of the Information Society
Citation: Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, June, 2018, 186p-195p
Series/Report no.: ADIS;2018
Abstract: With the rapid development of information technology and the expansion of the Internet, social network users and bloggers generate a huge amount of emotionally rich text. The automatic classification of emotions in the text is an area of interest to both social sciences and applications, such as the discovery of attitudes towards a given product. This paper presents and explores the machine learning methods used to classify emotions in the text. A comparative study of the effectiveness of the classification of the main methods of solving this task has been made. It also presents results from a study of correlations between the main types of emotions in the text.
Description: Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, June, 2018
ISSN: 1314-0752
Appears in Collections:ADIS 2018

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