# Evaluate the Tweet Analysis with Improved Accuracy Using Multi Channel N-gram Convolutional Neural Network Model over Naive Bayes Model

### Chinthapalli Reddy, P. Sriramaya

#### 2023

#### Abstract

The purpose of this study is to compare the accuracy of tweet analysis using a novel Multi Channel N-gram CNN model and Naive Bayes model. Materials and Methods: There are two groups in this study: Naive Bayes methods and Multi channel N gram CNN. The sample size for each group is 10, and the study’s parameters include an alpha value of 0.8 and a beta value of 0.2. Taking the G-Power value of 80% into account, the significance value of the dataset was predicted using SPSS. Results and Discussion:In the examination of tweets, the Multi Channel N gram CNN Algorithm’s accuracy was 97.84%, whereas the Naive Bayes algorithm’s accuracy was 79.69%; this means that the two algorithms are statistically different. Conclusion: When analyzing tweets, the Multi Channel N gram CNN algorithm performs noticeably better than the Naive Bayes algorithm.

Download#### Paper Citation

#### in Harvard Style

Reddy C. and Sriramaya P. (2023). **Evaluate the Tweet Analysis with Improved Accuracy Using Multi Channel N-gram Convolutional Neural Network Model over Naive Bayes Model**. 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 546-552. DOI: 10.5220/0012772600003739

#### in Bibtex Style

@conference{ai4iot23,

author={Chinthapalli Reddy and P. Sriramaya},

title={Evaluate the Tweet Analysis with Improved Accuracy Using Multi Channel N-gram Convolutional Neural Network Model over Naive Bayes Model},

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={546-552},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0012772600003739},

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 - Evaluate the Tweet Analysis with Improved Accuracy Using Multi Channel N-gram Convolutional Neural Network Model over Naive Bayes Model

SN - 978-989-758-661-3

AU - Reddy C.

AU - Sriramaya P.

PY - 2023

SP - 546

EP - 552

DO - 10.5220/0012772600003739

PB - SciTePress