Open AccessIntensity Weight Factor Based Sentiment Prediction Analysis on Tweets
Author(s) -
M. N.,
M. C. Padma
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d9590.018520
Subject(s) - sentiment analysis , computer science , naive bayes classifier , field (mathematics) , machine learning , artificial intelligence , social media , emotion detection , natural language processing , data science , support vector machine , emotion recognition , world wide web , mathematics , pure mathematics
Advances in the field of sentiment analysis are quick and purposeful to explore the views or articles available on various social media platforms through the techniques of machine learning with emotions, topic analysis or polarization calculations. Although employing various machine learning techniques and emotion analysis tools, there is a direct need for modern methods. To address these challenges, the contribution of this paper involves adopting a new approach that includes emotional analysts that integrates emotional intensity and machine learning. In addition, this document also provides a comparison of sentiment analysis techniques in analyzing political views through the application of machine learning algorithms such as Naive Bayes and KNN.