Deep Sentiment Analysis: A Case Study on Stemmed Turkish Twitter Data

Deep Sentiment Analysis: A Case Study on Stemmed Turkish Twitter Data

Sentiment analysis using stemmed Twitter data from various languages is an emerging research topic. In this paper, we address three data augmentation techniques namely Shift, Shuffle, and Hybrid to increase the size of the training data; and then we use three key types of deep learning (DL) models n...

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Bibliographic Details
Main Authors: Harisu Abdullahi Shehu, Md. Haidar Sharif, Md. Haris Uddin Sharif, Ripon Datta, Sezai Tokat, Sahin Uyaver, Huseyin Kusetogullari, Rabie A. Ramadan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Data augmentation
deep learning
machine learning
neural networks
sentiment analysis
Turkish
Online Access:https://ieeexplore.ieee.org/document/9395633/

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