Sentiment Analysing of Twitter Database Using K-Means Hierarchical Clustering and SVM Algorithm

Abstract

Many businesses use social media networks to provide various services, communicate with
clients, and gather information about people's thoughts and opinions. Emotional analysis is a
form of machine learning that finds variation such as positive or negative ideas in a text,
complete text, paragraphs, lines, or paragraphs. Machine learning (ML) is a multidisciplinary
component that combines mathematical and computer science methods to improve guessing
and differentiation algorithms. In this work, the sentimental type is analysed by using k-means
and k-means hierarchical clustering algorithm and accuracy score is predicted by classifying
using SVM. A score of 94.86% is obtained as KCH accuracy score.