Top Data Science Project – Sentiment Analysis Project

Today, we are starting our series of R projects and the first one is Sentiment analysis. So, in this article, we will develop our very own project of sentiment analysis using R. We will make use of the tiny text package to analyze the data and provide scores to the corresponding words that are present in the dataset. In the end, you will become industry ready to solve any problem related to R programming.

R Project – Sentiment Analysis

The aim of this project is to build a sentiment analysis model which will allow us to categorize words based on their sentiments, that is whether they are positive, negative and also the magnitude of it. Before we start with our R project, let us understand sentiment analysis in detail.

What is Sentiment Analysis?

Sentiment Analysis is a process of extracting opinions that have different polarities. By polarities, we mean positive, negative or neutral. It is also known as opinion mining and polarity detection. With the help of sentiment analysis, you can find out the nature of opinion that is reflected in documents, websites, social media feed, etc. Sentiment Analysis is a type of classification where the data is classified into different classes. These classes can be binary in nature (positive or negative) or, they can have multiple classes (happy, sad, angry, etc.).

If you are not aware of the topic classification in R, here is the best guide 

Developing our Sentiment Analysis Model in R

We will carry out sentiment analysis with R in this project. The dataset that we will use will be provided by the R package ‘janeaustenR’.

In order to build our project on sentiment analysis, we will make use of the tidytext package that comprises of sentiment lexicons that are present in the dataset of ‘sentiments’.

Sentiment analysis (or opinion mining) is a natural language processing (NLP) technique used to determine whether data is positive, negative or neutral. Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiment in customer feedback, and understand customer needs

Summary

In this blog, we went through our project of sentiment analysis in R. We learnt about the concept of sentiment analysis and implemented it over the dataset of Jane Austen’s books. We were able to delineate it through various visualizations after we performed data wrangling on our data. We used a lexical analyzer – ‘bing’ in this instance of our project. Furthermore, we also represented the sentiment score through a plot and also made a visual report of wordcloud.

Hope you enjoyed this R Sentiment Analysis Project. Drop your queries through comments, we will definitely help.

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