MSATS: Multilingual sentiment analysis via text summarization

Sentiment Analysis has been a keen research area for past few years. Though much of the exploration that has been done supports English language only. This paper proposes a method using which one can analyze different languages to find sentiments in them and perform sentiment analysis. The method leverages different techniques of machine learning to analyze the text. Machine translation is used in the system to provide with the feature of dealing with different languages. After the machine translation, text is processed for finding the sentiments in the text. With the advent of blogs, forums and online reviews there is substantial text present on internet that can be used to analyze the sentiment about a particular subject or an object. Hence to reduce the processing it is beneficial to extract the important text present in it. So the system proposed uses text summarization process to extract important parts of text and then uses it to analyze the sentiments about the particular subject and its aspects.