![]() For performance evaluation support vector machine, naïve bayes, k-nearest neighbor and neural network classifiers are used to classify the popular and unpopular data. In this work, the result analysis is performed by applying Co-relation algorithm, particle swarm optimization and principal component analysis. ![]() The work presented in this study aims to find the best model to predict the popularity of online news using machine learning methods. It is therefore necessary to build an automatic decision support system to predict the popularity of the news as it will help in business intelligence too. The popularity of online news depends on various factors such as the number of social media, the number of visitor comments, the number of Likes, etc. ![]() News popularity is the maximum growth of attention given for particular news article.
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