SentiXGboost: enhanced sentiment analysis in social media posts with ensemble XGBoost classifier-Reference-Cited by-同舟云学术

SentiXGboost: enhanced sentiment analysis in social media posts with ensemble XGBoost classifier

Published:2021-06-28 Issue:6 Volume:44 Page:562-572
ISSN:0253-3839
Container-title:Journal of the Chinese Institute of Engineers
language:en
Short-container-title:Journal of the Chinese Institute of Engineers

Author:

Hama Aziz Roza Hikmat¹²,Dimililer Nazife³

Affiliation:

1. Faculty of Arts & Sciences, Department of Applied Mathematics & Computer Science, Eastern Mediterranean University (EMU), Famagusta, North Cyprus, Mersin 10 Turkey

2. Department of Computer Science, College of Basic Education, University of Sulaimani, Iraq

3. School of Computing and Technology, Department of Information Technology, Eastern Mediterranean University (EMU), Famagusta, North Cyprus, Mersin 10 Turkey

Publisher

Informa UK Limited

Subject

General Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/02533839.2021.1933598

Reference49 articles.

1. The Impact of Features Extraction on the Sentiment Analysis

2. Successes and challenges in developing a hybrid approach to sentiment analysis

3. A Machine Learning Based Approach for Opinion Mining on Social Network Data

4. Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model

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