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Sentiment Analysis in R


What will you learn today?

What is Sentiment Analysis?

Sentiment Analysis Use Cases

Sentiment Analysis Tools

Hands-On : Sentiment Analysis in R


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.


Sentiment Analysis Use Cases


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


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


Tools implementing Sentiment Analysis


Sentiment Analysis : Customer Acquisition

Salesforce have built a product called Radian6 whichidentifies conversations that happen on social media about a particular company, its products or its competitors.

Salesforce Radian6


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


Sentiment Analysis Tools

Below are some of the popular sentiment analysis tools :


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.)


Hands-onSentiment Analysis in R


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Download - Sentiment Analysis in R

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