Paper Title
Sentiment Analysis Of News Articles Using Machine Learning Approach

Abstract
Determining the attitude of a writer with Respect to some topic or the overall feeling in a document is basic aim of doing sentiment analysis. News analysis can be used to plot the firm’s behavior over time and thus yield important strategic insights about firms. Sentiment analysis is also useful in social media monitoring to automatically characterize the overall feeling or mood of consumers as reflected in social media toward a specific brand or company and determine whether they are viewed positively or negatively. In our work, we focus on news articles. News analysis and news sentiment calculations are now routinely used by both buy-side and sell-side in market surveillance and compliance. The main tasks identified for news opinion mining consists of extracting sentences from online published news articles that mentions company news, and identifying positive and negative sentiment that exist in that article and further summarizing the article polarity. A large number of companies use news analysis to help them make better business decisions so in our project we are doing sentiment analysis on news article related to company. Keywords- Machine Learning, Natural Language Processing, Opinion Mining, News Analysis.