• FARZIZ AKTAR AHMED
• JUNUMONI KHAKHLARI
• NITUMANI SARMAH

Every year 703000 people committed suicide globally because of different reasons. Uses of smartphone has rapidly increased, and people are interacting with others using social media and other platforms has increased as a result. These social media data can be use as raw data to perform sentient analysis to understand the sentiment. In recent few years sentiment analysis has gain so much of popularity. Many studies have been done already to analyze and understand sentiment behind a statement. And there are still many research in progress to analyze the sentiment. This paper acknowledged that many researchers have done their works by using Machine learning and Natural Language Processing (NLP). This research work explored a various numbers research paper related to sentiment analyze of suicidal statements and the methodology they have used and trying to find out the more possibilities to improve the possible outcome with more accuracy. This paper included a table [ Table - 1] of past work. All the works has been done by the researchers on sentiment analysis in different field, but the accuracy of the result is, yet a problem need to be solved. This research work witnesses that there are very rare works done by using Ensemble Model. To solve this problem, this research work prefers to implement ensemble model to improve the accuracy. So, using this model, we can achieve a great level of accuracy. So, this is the field need to be explored more, also to find out the best algorithm in existing work and to improve the same.

Sentiment Analysis, Suicide attempts, Ensemble Model, Machine Learning. Decision Tree. SVM, Naïve Bayes.

"A Review On Analysis Of Suicidal Notes Sentiment Rich Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.f21-f30, May-2022, Available :http://www.jetir.org/papers/JETIR2205604.pdf

"A Review On Analysis Of Suicidal Notes Sentiment Rich Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppf21-f30, May-2022, Available at : http://www.jetir.org/papers/JETIR2205604.pdf