sentiment analysis via r programming

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Sentiment Analysisvia R Programming


Session Objectives

In this session you would learn and understand

ᗍ What is R?ᗍ R for Data Analysisᗍ Achieving Business challenges via Rᗍ Benefits of R for Businessᗍ What is Sentiment Analysis?ᗍ Advantages of Sentiment Analysisᗍ 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 analysisᗍ Interactive languageᗍ Data structuresᗍ Graphicsᗍ Missing valuesᗍ Functions as first class objectsᗍ Packagesᗍ 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 Attitudesᗍ Emotionsᗍ 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 smileyNegative words

with positive smiley


Example

People’s opinion towards a movie have huge impact on its successHigh 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

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