Sentiment Analysis via R Programming

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Sentiment Analysis
via R Programming

Session Objectives
In this session you would learn and understand
ᗍ What is R?
ᗍ R for Data Analysis
ᗍ Achieving Business challenges via R
ᗍ Benefits of R for Business
ᗍ What is Sentiment Analysis?
ᗍ Advantages of Sentiment Analysis
ᗍ Applications of Sentiment Analysis

Not really !!!!
Introduction

What is R?
R is a language and environment for statistical computing and graphics
It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories
(formerly AT&T, now Lucent Technologies) by John Chambers and colleagues
R helps people perform a wide variety of computing tasks by giving them access to various commands
Source: http://www.r-project.org/about.html

Why R for Data Analysis?
ᗍ R is not the only language that can be used for data analysis
ᗍ Interactive language
ᗍ Data structures
ᗍ Graphics
ᗍ Missing values
ᗍ Functions as first class objects
ᗍ Packages
ᗍ Community

ᗍ Develop your statistical and analytical skills in the R programming environment
ᗍ Acquire a thorough understanding of the R programming source environment, and use your skills in statistics
and R to solve a variety of complex problems
Today, it is imperative for every modern business to understand the huge amounts of data it maintains on
its customers and itself
Achieving Business Challenges in R
R allows the business to easily and quickly clean and explore the information that it wants to analyse
R allows the business to explore new information with the help of customized visualizations

Use Case
Problem Statement:
A major benefit of social media is that we can see the good and bad things people say about a particular brand or
personality
The bigger your company gets difficult it becomes to keep a handle on how everyone feels about your brand. For
large companies with thousands of daily mentions on social media, new sites and blogs, it is extremely difficult to
do this manually

Use Case - Solution
Sentimental analysis using R can solve this problem
Sentimental Analysis helps to evaluate the people’s sentiment about particular brand or personality in business
Solution:
Let us know what is sentimental analysis and steps involved to solve the problem

What are Sentiments?
Sentiment = feelings
ᗍ Attitudes
ᗍ Emotions
ᗍ Opinions
Subjective impressions, not facts

Why Sentiment Analysis?
The amount of user-generated content on the Internet has risen exponentially over the last decade and such content is
now always at our fingertips
ᗍ Sentiment analysis is in demand because of its efficiency – thousands of text documents can be processed for
sentiment in seconds, compared to the hours it would take when done manually
ᗍ Huge amounts of ‘sentiments’ are available from social media including Twitter, Facebook, message boards,
blogs, and user forums

What is Sentiment Analysis?
ᗍ Sentiment is an R package with tools for sentiment analysis for positivity/negativity and emotion classification
ᗍ Sentiment Analysis provides a rich set of tools and techniques for extracting information from large dataset and
summarizing it
Example: Service providers use Sentiment Analysis to quickly assess how new products and features are being
received
Sentiment Analysis uses natural language processing, text analysis and computational linguistics to identify and
extract subjective information from text

Questions Sentiment Analysis might ask
ᗍ Is this product review positive or negative?
ᗍ Is this customer email satisfied or dissatisfied?
ᗍ Based on a sample of tweets, how are people responding to this ad campaign/product release/news item?
ᗍ How have bloggers' attitudes about the president changed since the election?

Data Collection in Sentiment Analysis
Data Collection
For performing sentimental
analysis we need Twitter data
consisting of tweets about a
particular brand
For collecting the data and
tweets we have used Twitter
API available for free
Data Collection
Remove unwanted words
which does not come under
sentiments such as,
Emotions, urls, usernames,
hashtags, repeated letters
Data Collection
Two way categorization:
Positive or Negative
Data Collection
Positive words with
negative smiley
Negative words with
positive smiley

Example
People’s opinion towards a movie have huge impact on its success
High volume of positive tweets indicate success of movie
How to quantify?
Lets take a set of movies and check for ratio of positive and negative tweets

Example: Tweets

Result using Sentimental Analysis
This graph makes us to easily understand the
result ratios, than to check directly with the
sites

Who Uses R? – Domains
Telecom Pharmaceuticals Financial Industry
and many more…

Who Uses R? – Companies

Job Trends – R Programming

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Sentiment Analysis via R Programming

Sentiment Analysis via R Programming

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