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ID 113250
Author
Fujino, Naoya Tokushima University
Keywords
emotion estimation
user's gender
deep neural networks
Content Type
Journal Article
Description
In this study, we focus on Twitter as a representative SNS and target emotion estimation from tweets posted on Twitter by male and female users. Specifically, we construct gender-based emotion estimation models assuming that there are different word usage tendencies between genders. By analyzing gender-specific differences in the use of emotion-related slang and emoji, we propose a method to improve emotion estimation based on neural networks using a different distributed representation model for each gender. Our evaluation experiments show that training with Deep Convolutional Neural Networks using word's distributed representation as the feature produced higher estimation accuracy than training with Feed Forward Neural Networks.
Journal Title
International Journal of Advanced Intelligence
ISSN
18833918
Publisher
AIA International Advanced Information Institute
Volume
10
Issue
1
Start Page
121
End Page
133
Published Date
2018-03
EDB ID
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology