2023
doi: 10.12720/jait.14.6.1331-1338
A Framework for Youth Sentiment Analysis Using Natural Language Processing
Rasha A. ElStohy1,2
- 1Department of Information Systems, Obour Institutes, EL Sharqia, Egypt
- 2Department of Information Communication Technology, New Cairo Technological University, Cairo, Egypt
- Manuscript receivedApril 3, 2023
- revisedMay 10, 2023
- acceptedJune 19, 2023
- publishedDecember 1, 2023
Abstract
Social networks are currently the most widely used platforms for exchanging thoughts on various subjects or events, particularly those geared at young people. Consequently, the Natural Language Processing (NLP) industry has access to an abundant source of data provided by those applications. This paper presents a model for sentiment analysis using Naive Bayes algorithm. A proposed model is applied to two dataset samples to train, create, and test classification models. The supervised approach combined unigram for feature extraction and the Naive Bayes algorithm to extract the trending topics for youth Tweets. The model is evaluated on a test set during the worldwide crisis and is shown to be effective in predicting opinions on new reviews. The results of the evaluation demonstrate that the model is capable of accurately predicting opinions with a high degree of accuracy.
Keywords
- Natural Language Processing (NLP)
- sentiments
- social networks
- tweeter
- machine learning
How to Cite
Rasha A. ElStohy, "A Framework for Youth Sentiment Analysis Using Natural Language Processing," Journal of Advances in Information Technology, vol. 14, no. 6, pp. 1331-1338, 2023. https://doi.org/10.12720/jait.14.6.1331-1338
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
