@article {10.3844/jcssp.2022.832.840,
article_type = {journal},
title = {Psychological Behavior Prediction through Sentiment Analysis Technics: Transformers and ML Approach},
author = {Naji, Maryame and Daoudi, Najima and Ajhoun, Rachida},
volume = {18},
number = {9},
year = {2022},
month = {Sep},
pages = {832-840},
doi = {10.3844/jcssp.2022.832.840},
url = {https://thescipub.com/abstract/jcssp.2022.832.840},
abstract = {In the era of the COVID-19 epidemic, governmentshave imposed nationwide lockdowns, which make a huge change to people's dailyroutines. This last impacts indirectly the well-being of people's mentalhealth. And due to social media, many conversations about these phenomena occuronline, especially those related to people's emotions. Which brought challengesand opportunities for sentiment analysis researchers. In this article, we areinterested in extracting correlations between this epidemic and itspsychological effects by analyzing users' tweets through common Deep Learningand Machine Learning approaches used for text classification. This last goal isa crucial step to fulfill the main objective of our research: Developing anintelligent system that provides recommendations such as positive support andearly alert to help people in case of specific needs particularly challengingmental states.  },
journal = {Journal of Computer Science},
publisher = {Science Publications}
}