The Natural Language API is one of the machine learning models that can analyze syntax, extract entities, and evaluate the sentiment.

1. Mohammed Adnan
AI student at IAU
Entity and Sentiment
Analysis
Start at 08:05 pm

4. What is Sentiment Analysis?
What is Entity Analysis?
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Entity and Sentiment

5. Entity and Sentiment Analysis

6. Entity and Sentiment Analysis
Entity
Analysis
Entity Analysis inspects
the given text for known
entities (proper nouns
such as public figures,
landmarks, etc.), and
returns information about
those entities.
sentiment analysis and
attempts to determine
the sentiment (positive
or negative) expressed
about entities
Sentiment
Analysis

7. Example of Entity
and sentiment
Analysis

8. Example of Entity and Sentiment Analysis
“I don’t find the app useful: it’s really slow and
crashing”.
Entity Sentiment
1- App 1- I don’t find the app useful
2- it’s really slow and crashing
Negative

9. Example of Entity and Sentiment Analysis
“I really like the new design of your website!”.
Entity Sentiment
1- design
2- website
1- I really like the new
design of your website
Positive

10. Example of Entity and Sentiment Analysis
“I’m not sure if I like the new design”.
Entity Sentiment
1- design 1- I’m not sure if I like the
new design
Natural

11. Product Sentiment
https://app.monkeylearn.com/main/classifier
s/cl_TWmMTdgQ/tab/demo/
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12. Application of Entity
and sentiment
Analysis

13. Application of Entity and Sentiment Analysis
Twitter amazon Facebook

14. Importance of Entity
and Sentiment
analysis

15. Importance of Entity and Sentiment Analysis
Social Media.
02
Market Research.
01
Brand Monitoring.
03

16. Market Research
If you are planning to release a new
product, and you want to collect
insights on people’s attitudes,
experiences, and needs related to the
field of your product, you could use
sentiment analysis to track different
sources of online conversations about a
given topic. The same thing applies for
following new trends.

17. Market Research

18. Social Media
Imagine you just launched a new
product feature and notice a sharp
increase in mentions on Twitter. Are
customers tweeting more because they
are delighted with the new feature? Or,
are they actually complaining about the
feature? Performing sentiment analysis
on Twitter data can help you quickly
understand the tone of those mentions.
Sentiment analysis is particularly useful
for social media monitoring because it
goes beyond the number of likes or
retweets, by providing qualitative
insights.

19. Brand Monitoring
Besides social media, online
conversations can take place in blogs,
review websites, news websites and
forum discussions. Product reviews, for
instance, have become a crucial step in
the buyer decision process. Consumers
read at least ten reviews before buying,
and 57% will only trust a business if it’s
rated with 4 or more stars.

20. Google Cloud
Platform
Suit of computing services provided by google.

21. Entity and Sentiment
analysis

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Lab:
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26. Mohammed Adnan
Speakers
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@DSC_IAU @753mohamed #machine_learning_IAU