analyzing movie reviews sentiment in this we continue with our focus on case-study oriented where we will focus on specific real-world problems and scenarios and how we can use machine learning to solve them we will cover aspects pertaining to natural language processing (nlp)text analyticsand machine learning in this the problem at hand is sentiment analysis or opinion miningwhere we want to analyze some textual documents and predict their sentiment or opinion based on the content of these documents sentiment analysis is perhaps one of the most popular applications of natural language processing and text analytics with vast number of websitesbooks and tutorials on this subject typically sentiment analysis seems to work best on subjective textwhere people express opinionsfeelingsand their mood from real-world industry standpointsentiment analysis is widely used to analyze corporate surveysfeedback surveyssocial media dataand reviews for moviesplacescommoditiesand many more the idea is to analyze and understand the reactions of people toward specific entity and take insightful actions based on their sentiment text corpus consists of multiple text documents and each document can be as simple as single sentence to complete document with multiple paragraphs textual datain spite of being highly unstructuredcan be classified into two major types of documents factual documents that typically depict some form of statements or facts with no specific feelings or emotion attached to them these are also known as objective documents subjective documents on the other hand have text that expresses feelingsmoodsemotionsand opinions sentiment analysis is also popularly known as opinion analysis or opinion mining the key idea is to use techniques from text analyticsnlpmachine learningand linguistics to extract important information or data points from unstructured text this in turn can help us derive qualitative outputs like the overall sentiment being on positiveneutralor negative scale and quantitative outputs like the sentiment polaritysubjectivityand objectivity proportions sentiment polarity is typically numeric score that' assigned to both the positive and negative aspects of text document based on subjective parameters like specific words and phrases expressing feelings and emotion neutral sentiment typically has polarity since it does not express and specific sentimentpositive sentiment will have polarity and negative of courseyou can always change these thresholds based on the type of text you are dealing withthere are no hard constraints on this in this we focus on trying to analyze large corpus of movie reviews and derive the sentiment we cover wide variety of techniques for analyzing sentimentwhich include the following unsupervised lexicon-based models traditional supervised machine learning models newer supervised deep learning models advanced supervised deep learning models (cdipanjan sarkarraghav bali and tushar sharma sarkar et al practical machine learning with python