IRO Journals

Journal of Artificial Intelligence and Capsule Networks

Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3

Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
Volume-3 | Issue-3

Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4

Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3

Hybrid Parallel Image Processing Algorithm for Binary Images with Image Thinning Technique
Volume-3 | Issue-3

Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4

QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
Volume-3 | Issue-3

Probabilistic Neural Network based Managing Algorithm for Building Automation System
Volume-3 | Issue-4

Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
Volume-3 | Issue-1

Artificial Bee Colony Optimization Algorithm for Enhancing Routing in Wireless Networks
Volume-3 | Issue-1

Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4

Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3

Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1

Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3

Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
Volume-3 | Issue-4

Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4

Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4

Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4

Artificial Intelligence Algorithm with SVM Classification using Dermascopic Images for Melanoma Diagnosis
Volume-3 | Issue-1

An Efficient Machine Learning based Model for Classification of Wearable Clothing
Volume-3 | Issue-4

Home / Archives / Volume-3 / Issue-3 / Article-1

Volume - 3 | Issue - 3 | september 2021

Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Milan Tripathi   487  288
Pages: 151-168
Cite this article
Tripathi, M. (2021). Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM. Journal of Artificial Intelligence and Capsule Networks, 3(3), 151-168. doi:10.36548/jaicn.2021.3.001
Published
23 July, 2021
Abstract

The government's months-long total lockdown in response to the COVID19 outbreak has resulted in a lack of physical connection with others. This resulted in a massive increase in social media communication. Twitter has become one of the most popular places for people to communicate their thoughts and opinions. As a result, massive amounts of data are created every day. These data can assist businesses in making better judgments. In the case of Nepal, there has been relatively little investigation into the text's analysis. Because few researchers are working in the field, development is slow. In this study, Four language-based models for sentiment analysis of Nepali covid19 tweets are designed and evaluated. Because the number of individuals using social media is expected to skyrocket in the next few days, companies will benefit from an AI-based sentiment analysis system. It will greatly assist firms in adapting to the changing climate.

Keywords

COVID19 social media Twitter sentiment analysis artificial intelligence

Full Article PDF Download Article PDF 
×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

Subscription Payment Details

townscript (INR / USD): click here

Subscription Fee

Annual Subscription 15,000 INR / 200 USD
Subscription form: click here