Sentiment Analysis in R

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Sentiment Analysis in R

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What will you learn today?
 What is Sentiment Analysis?
 Sentiment Analysis Use Cases
 Sentiment Analysis Tools
 Hands-On : Sentiment Analysis in R

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What is Sentiment Analysis?
Sentiment Analysis also called Opinion Mining implies extracting opinions, emotions and
sentiments from data.
Sentiment analysis is widely used to track attitudes and feelings on the web especially
for measuring performance of products, services, brands.

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Sentiment Analysis Use Cases

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Sentiment Analysis : Airline Industry
Delta is an American airline which
monitors tweets to find out how their
customers feel about delays, upgrades,
in-flight entertainment and more.
For example when a customer tweets
negatively about his experience, Delta
identifies such negative tweets and
figure out the problem to improve the
customer’s experience
Delta Airline

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Sentiment Analysis : Retail Chain
Macy’s is an American chain of
department stores, Macy’s
uses sentiment analysis as one
of the way to improve
customer experience and
business growth.
Macy’s

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Tools implementing Sentiment Analysis

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Sentiment Analysis : Customer Acquisition
Salesforce have built a
product called Radian6 which
identifies conversations that
happen on social media about
a particular company, its
products or its competitors.
Salesforce Radian6

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Sentiment Analysis : Financial Analysis
Thomson Reuters EIKON
software uses Sentiment
Analysis to gain competitive
advantage by analyzing the
social media tweets/posts
about various companies and
people
Thomson Reuters EIKON

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Sentiment Analysis Tools
Below are some of the popular sentiment analysis tools :

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Sentiment Analysis in R
Below are the steps to perform sentiment analysis in R
1. Load the data
2. Create a list of positive words
3. Create a list of negative words
4. Apply the sentiment algorithm
5. Analyze the result (e.g. frequency distribution, mean, median, histogram etc.)

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Hands-on
Sentiment Analysis in R

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