• Tidak ada hasil yang ditemukan

Sentiment Analysis from Bengali Depression Dataset using Machine Learning

N/A
N/A
Info
Unduh - Bebas
Protected

Academic year: 2024

Membagikan "Sentiment Analysis from Bengali Depression Dataset using Machine Learning"

Copied!
1
0
0

Memuat.... (Lihat teks lengkap sekarang)

Unduh sekarang ( 1 Halaman )

Teks penuh

(1)

Sentiment Analysis from Bengali Depression Dataset using Machine Learning

Md. Rafidul Hasan Khan, Umme Sunzida Afroz, Abu Kaisar Mohammad Masum, Sheikh Abujar, Syed Akhter Hossain

Abstract

Nowadays, Sentiment Analysis is one of the advanced matters of natural language processing. Sentiment analysis determines a particular pole of a paragraph. Our purpose is to find the sentiment from the Bengali paragraph which is happy or sad using various types of machine learning classification analysis algorithms. For doing this we are collecting data from various social network sites, Bengali blogs, etc. To get a compatible result, we passed through many difficulties. Bengali text preprocessing is one of the complex parts of all. After preprocessing the data, we tokenized the data by using Countvectorizer. After that, we applied six different algorithms to predict almost high accuracy. Among them, the Multinomial Naive Bayes provide us the maximum accuracy which is 86.67%

Keywords: Natural Language Processing, Sentiment Analysis, Depression Detection, Text Preprocessing, Social Media, Multinomial Naive Bayes

DOI: 10.1109/ICCCNT49239.2020.9225511 Conference / Journal Link

https://ieeexplore.ieee.org/document/9225511

Referensi

Unduh sekarang ( DOCX - 1 Halaman - 12.81 KB )

Dokumen terkait

View of The Sentiment Analysis Using Naïve Bayes with Lexicon-Based Feature on TikTok Application

The novelty of the study is the sentiment analysis using Naive Bayes with Lexicon-Based feature was performed on TikTok user reviews on Google Play Store unlike the previous

Sentiment Analysis From Twitter About Covid-19 Vaccination in Indonesia Using Naive Bayes and Xgboost Classifier Algorithm

This sentiment analysis process uses the Classification method with the Naive Bayes Classifier and will be compared with the XGBoost Classifier algorithm.. The results of this

View of SENTIMENT ANALYSIS WITH A CASE STUDY OF PRACTICE CARD ON TWITTER SOCIAL MEDIA USING NAIVE BAYES METHOD

Where it is necessary to do a research on sentiment analysis regarding the Pre-Employment Card on Twitter using the naive Bayes method to find out the positive and negative

Evaluation of E-learning Activity Effectiveness in Higher Education Through Sentiment Analysis by Using Naïve Bayes Classifier

Evaluation of E-learning Activity Effectiveness in Higher Education Through Sentiment Analysis by Using Naïve Bayes Classifier shows that the training set which contain the word

SENTIMENT ANALYSIS OF CUSTOMER, BASED ON CUSTOMER REVIEWS IN BANGLA LANGUAGE USING MACHINE LEARNING

4.2 Experimental Results and Analysis We have used supervised algorithms like Decision tree, Naive Bayes, Random Forest, Support Vector Machine SVM, K-Nearest Neighbors KNN and

Sentiment Analysis from Bangla Text Review Using Feedback Recurrent Neural Network Model

Sentiment Analysis from Bangla Text Review Using Feedback Recurrent Neural Network Model Pratim Saha, Naznin Sultana Abstract Sentiment analysis is one of the most discussed topics

Sentiment Analysis of Simobi Plus Mobile Application Using Naïve Bayes Classification

This study uses sentiment analysis using the Naive Bayes method to capture positive and negative sentiments for comments on the Simobi Plus mobile banking application on the Google Play

DETECTING SOCIAL MEDIA CYBERBULLYING ON BANGLA LANGUAGE USING MACHINE LEARNING

I've used many a type of algorithms like Natural Language Processing NLP, Logistic Regression LR, Multinomial Naïve Bayes MNB, Support Vector Classifier SVC, Random Forest Classifier