1. Artificial Intelligence fuelled Sentiment AnalysisBy
Tuhin Chattopadhyay, Ph.D.
Associate Director – Advanced Analytics Consulting
Nielsen,  Bengaluru
Artificial Intelligence & Machine Learning Summit
Bengaluru, India
10th November, 2017

2. Leisure Hours Adventure Sports Read Books on Personality Connoisseur
Play with Dogs
Golf
Chess
Adventure Sports
Scuba Diving
Paragliding
River Rafting
Read Books on
Positive Psychology
Advanced Statistics
Non-Fiction
Personality
Religiously Unaffiliated Theist
Spiritual
Philosophical/ Thinker
Connoisseur
Modern Art
Western Classical Music
Red Wine
Profession
Data Scientist
Academician
Researcher

3. Agenda Machine Intelligence for Sentiment Analysis
Machine Learning for Sentiment Analysis
Machine Intelligence for Sentiment Analysis

4. Section A: Machine Learning for Sentiment Analysis

5. What is Sentiment Analysis
Reference:
Title of the Paper: Sentiment analysis algorithms and applications: A survey
Authors: Walaa Medhat, Ahmed Hassan and Hoda Korashy
Journal: Ain Shams Engineering Journal, Volume 5, Issue 4, December 2014, Pages
Website:

6. Traditional Sentiment Analysis
Reference:
Title of the Paper: Sentiment analysis algorithms and applications: A survey
Authors: Walaa Medhat, Ahmed Hassan and Hoda Korashy
Journal: Ain Shams Engineering Journal, Volume 5, Issue 4, December 2014, Pages
Website:

7. Machine Learning Techniques for Sentiment Analysis
Reference:
Title of the Paper: Sentiment analysis algorithms and applications: A survey
Authors: Walaa Medhat, Ahmed Hassan and Hoda Korashy
Journal: Ain Shams Engineering Journal, Volume 5, Issue 4, December 2014, Pages
Website:
Image Source:

8. Section B: Machine Intelligence for Sentiment Analysis

9. Digital Assistants

10. Chatbots

11. Benefits of Chatbots
Chatbots for customer service will help businesses save $8 billion per year by 2022

12. How AI can help Chatbots? Anatomy of a Bot
Image Source : blog.wizeline.com

13. Tone Analyzer for Customer Engagement - 1

14. Tone Analyzer for Customer Engagement - 2

15. Tone Analyzer
I hate these new features On #ThisPhone after the update.
I hate #ThisPhoneCompany products, you'd have to torture me to get me to use #ThisPhone.
The emojis in #ThisPhone are stupid.
#ThisPhone is a useless, stupid waste of money.
#ThisPhone is the worst phone I've ever had - ever 😠.
#ThisPhone another ripoff, lost all respect SHAME.
I'm worried my #ThisPhone is going to overheat like my brother's did.
#ThisPhoneCompany really let me down... my new phone won't even turn on.

16. Document Level Analysis

17. Sentence Level Analysis

18. Text Analyzer
In 2009, Elliot Turner launched AlchemyAPI to process the written word, with all of its quirks and nuances, and got immediate traction. That first month, the company's eponymous language-analysis API processed 500,000 transactions. Today it's processing three billion transactions a month, or about 1,200 a second. “That's a growth rate of 6,000 times over three years,” touts Turner. “Context is super-important,” he adds. “'I'm dying' is a lot different than 'I'm dying to buy the new iPhone.'” “As we move into new markets, we're going to be making some new hires," Turner says. "We knocked down some walls and added 2,000 square feet to our office.” “We're providing the ability to translate human language in the form of web pages and documents into actionable data,” Turner says. Clients include Walmart, PR Newswire and numerous publishers and advertising networks. “This allows a news organization to detect what a person likes to read about,” says Turner of publishers and advertisers.

19. Entity Analysis

20. Keyword Analysis – 1

21. Keyword Analysis – 2

22. Concept Analysis

23. Taxonomy Analysis

24. Document Emotion

25. Targeted Emotion

26. Target Phrase

27. Document Sentiment

28. Targeted Sentiment

29. Typed Relations

30. Typed Relations – Sentence

31. Relations

32. Classical NLP vs Deep Learning NLP
Image Source : blog.aylien.com

33. Application of Deep Learning Algorithms

34. Recurrent Neural Networks (RNN)
Neural Networks with a feedback loop
The previous time step’s hidden layer and final outputs are fed back into the network as part of the input to the next time step’s hidden layers. 
Machine Translation
Question Answering System
Image Captioning

35. Recursive Neural Networks
Idea: Recursively merge pairs of words/ phrase representations
Sentence/ Text classification
Relation extraction and classification
Spam detection
Categorization of search queries
Semantic relation extraction
Recurrent Neural Networks • Learning sequences of words/characters/anything. • A few well-known varieties: – “Plain vanilla” RNNs – Long Short Term Memory (LSTM) RNNs – Attention mechanisms • HOT right now for video scene descriptions, question and answer systems, and text.
40. Recurrent Neural Networks • RNN’s are different from convolutional nets in that their don’t only connect up and down. • They can connect sideways within the same layer. • There are even architectures that can go in both directions.

36. Thank You