Full Description
This Element provides a basic introduction to sentiment analysis, aimed at helping students and professionals in corpus linguistics to understand what sentiment analysis is, how it is conducted, and where it can be applied. It begins with a definition of sentiment analysis and a discussion of the domains where sentiment analysis is conducted and used the most. Then, it introduces two main methods that are commonly used in sentiment analysis known as supervised machine-learning and unsupervised learning (or lexicon-based) methods, followed by a step-by-step explanation of how to perform sentiment analysis with R. The Element then provides two detailed examples or cases of sentiment and emotion analysis, with one using an unsupervised method and the other using a supervised learning method.
Contents
1. Sentiment analysis: Background; 2. Methods for sentiment analysis; 3. How to do sentiment analysis with R; 4. Case study 1: A diachronic analysis of sentiments and emotions in the State of the Union Addresses; 5. Case study 2: A sentiment and emotion analysis of movie reviews; 6. Conclusion: Where we are and where we are heading; References.
