Sentiment Analysis of Film Reviews using Machine Learning Techniques

Abstract

A huge amount of data is generated everyday on the web and it is only going to increase as more and more people start using the internet. Because of social networking platforms, more and more people are able to express their opinion and their views on different topics such as writing reviews about what movies they watched on different social media platforms including sites like IMDB. Sorting through these reviews manually to determine whether a certain review is positive or negative is an impossible tasks. Hence, the need to automate this arises. To provide a solution to such problems there are many ways including Sentimental Analysis. Sentiment Analysis deals with interaction between machine such as computers and natural languages used by human beings in short we can say training machine in accordance to the problem statement. We can derive high quality information by using simple text entered by the user through different patterns and trends leading towards the output we expect by the various evaluations and interpretations, thus we categorise and cluster our text in respect to the problem statement we are dealing with. After that we compute our output by using the dataset we have using different models, algorithms, mathematical computations with comes under the category of computational linguistics. This field is mainly applied when we have to take reviews or survey from our customers on products or services. Sentimental Analysis is a relatively new variant in the research area. It basically refers to as the opinions or views of the different data that is being collected using surveys, comments and reviews over the web.