Title:
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EMOTION ANALYSIS OF TWEETS USING DEEP
LEARNING TECHNIQUES |
Author(s):
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Sahil Bhatnagar, Sagar Malik and Niladri Chatterjee |
ISBN:
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978-989-8533-92-0 |
Editors:
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Ajith P. Abraham and Jörg Roth |
Year:
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2019 |
Edition:
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Single |
Keywords:
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Emotion Analysis, Deep Learning, LSTM, Twitter |
Type:
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Full Paper |
First Page:
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69 |
Last Page:
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76 |
Language:
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English |
Cover:
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Full Contents:
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click to dowload
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Paper Abstract:
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Microblogging is one of the most prominent forms of communication among internet users today. These services offer
users a tool to share opinions on a plethora of issues and aspects of their lives, and hence, they are rich data sources for
textual analysis, and offer vast potential to gain insight into the way people communicate. We examine the task of emotion
analysis of twitter data and design a neural network architecture for the task of classifying each tweet into one of five
emotion categories: joy, sadness, anger, laughter and fear. We also show a method to automatically collect and tag a corpus
of data for emotion analysis. Our experiments showed that our models outperform current state of the art techniques for the
proposed problem. |
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