Emotion Detection from Text and Sentiment Analysis of Ukraine Russia War using Machine Learning Technique

• Published in: International journal of advanced computer science & applications Vol. 13; no. 12
• Main Authors: Maruf, Abdullah Al, Ziyad, Zakaria Masud, Haque, Md. Mahmudul, Khanam, Fahima
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 2022
• Subjects: Data mining; Emotion recognition; Emotions; Machine learning; Racism; Sentiment analysis; Ukraine; Russia
• ISSN: 2158-107X; 2156-5570
• DOI: 10.14569/IJACSA.2022.01312101

In the human body, emotion plays a critical func-tion. Emotion is the most significant subject in human-machine interaction. In economic contexts, emotion detection is equally essential. Emotion detection is crucial in making any decision. Several approaches were explored to determine emotion in text. People increasingly use social media to share their views, and researchers strive to decipher emotions from this medium. There has been some work on emotion detection from the text and sentiment analysis. Although some work has been done in which emotion has been recognized, there are many things to improve. There is not much work to detect racism and analysis sentiment on Ukraine -Russia war. We suggested a unique technique in which emotion is identified, and the sentiment is analyzed. We utilized Twitter data to analyze the sentiment of the Ukraine-Russia war. Our system performs better than prior work. The study increases the accuracy of detecting emotion. To identify emotion and racism, we used classical machine learning and the ensemble method. An unsupervised approach and NLP modules were used to analyze sentiment. The goal of the study is to detect emotion and racism and also analyze the sentiment.