Evaluation of Multi-Channel N-gram Convolutional Neural Network for Improved Tweet Analysis Accuracy

Chinthapalli Reddy, P. Sriramya

2023

Abstract

This study aimed to juxtapose the efficacy of the innovative Multi-Channel N-gram CNN model with the Naive Bayes model in tweet analysis. Two groups were established: the Naive Bayes and the Multi-Channel N-gram CNN, with each having a sample size of 10. The research parameters set were an alpha value of 0.8 and a beta value of 0.2. With a G-Power value of 80%, the significance of the dataset was ascertained using SPSS. Our findings highlighted that the Multi-Channel N-gram CNN algorithm achieved an accuracy of 97.84%, markedly outperforming the Naive Bayes which managed 79.69%. Consequently, for tweet analysis, the Multi-Channel N-gram CNN model is evidently superior.

Paper Citation

in Harvard Style

Reddy C. and Sriramya P. (2023). Evaluation of Multi-Channel N-gram Convolutional Neural Network for Improved Tweet Analysis Accuracy. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 51-57. DOI: 10.5220/0012544300003739

in Bibtex Style

@conference{ai4iot23,
author={Chinthapalli Reddy and P. Sriramya},
title={Evaluation of Multi-Channel N-gram Convolutional Neural Network for Improved Tweet Analysis Accuracy},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={51-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012544300003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Evaluation of Multi-Channel N-gram Convolutional Neural Network for Improved Tweet Analysis Accuracy
SN - 978-989-758-661-3
AU - Reddy C.
AU - Sriramya P.
PY - 2023
SP - 51
EP - 57
DO - 10.5220/0012544300003739
PB - SciTePress