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Impetus Technologies Inc. 
Building a Sentiment Analytics 
Solution Powered by Machine 
© 2014 1 Impetus Technologies 
Learning 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Outline 
• Sentiment Analysis – Why? 
• Solution landscape 
• Addressing challenges with Machine Learning 
• Building a sentiment analytics solution 
– Leveraging Machine learning and n-gram 
• Case Studies 
© 2014 2 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Sentiment Analysis 
• Determines the attitude of a speaker or a writer with 
respect to a particular subject, event or campaign 
• Computational study of opinions, sentiments, and 
emotions expressed in text 
© 2014 3 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Measuring Sentiments 
© 2014 4 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Current Solutions Landscape 
• Natural Language Processing 
– Deals with the actual text element 
– Transforms text into a format usable by machine 
• Artificial intelligence 
– Uses information by NLP and Mathematical calculations 
– Determines negative, positive or neutral sentiments 
– Used for clustering 
© 2014 5 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Sentiment Analysis: Challenges 
• Demystifying accuracy 
• Inability of machines to gauge and measure sentiments accurately 
• Isolating content types 
• Neutral nature of social media mentions 
• Sentiment override 
• User needs override control due to inaccuracy of automated sentiment 
measurement 
© 2014 6 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Machine Learning 
Intelligent structure that acquires and integrates 
Learns from experience, training, analytical observation 
© 2014 7 Impetus Technologies 
knowledge automatically 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Subjectivity Vs Sentiment 
Sentiment analysis - text classification problem 
• Segregate 
• Opinionated documents as per positive/ negative 
• Sentence or a clause of the sentence as subjective or 
objective 
• Subjective sentence or clause on the basis of positive, 
negative or neutral 
© 2014 8 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Determining Polarity 
Leveraging Machine Learning 
Algorithm identifies positive/ negative/neutral sentiments 
Refers knowledge bank to determine polarity of a new sentence or word 
A knowledge bank is the database of pre-trained words and sentences classified 
© 2014 9 Impetus Technologies 
as negative, neutral, positive 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Predicting Sentiment Intensity 
• Benchmark neutral - say 40-50% of positive is neutral 
– Intensity below the benchmark is negative and above is 
positive. 
• Referring Knowledge Bank 
– Continuously trained by a Machine Learning Algorithm 
– Intensity predictions becomes accurate 
Occurrence of a word or sequence of words in a particular polarity decides the 
© 2014 10 Impetus Technologies 
intensity of the overall sentiment 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
How it works? 
© 2014 11 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Text classification –n- gram 
© 2014 12 Impetus Technologies 
Result Report 
Ex: 
RUBBISH – Negative 
RUBBISHING – Negative 
RUBBISHED - Negative 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Building Knowledge Base 
© 2014 13 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Leveraging Machine Learning 
© 2014 14 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Impetus Solution 
• Intuitively retrieves input text for analysis 
• Processes various Low level APIs, REST APIs, enriched XML DOC, Text, 
© 2014 15 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58 
or RSS 
• Architecture enables exporting services in form of REST APIs 
• Intuitive solution, capable of processing near real-time data using Big 
Data stack 
• Concurrent processing system enables fast results with higher 
accuracy
What’s new? 
Higher accuracy 
Identifies influencers 
Reputation as per demographics 
Measuring sentiment intensity 
© 2014 16 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Case Studies 
Nokia Lumia (On Twitter) 
Apple’s iPad3 (On Facebook) 
© 2014 17 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Case study : Nokia 
• Search keyword - “Nokia Lumia” 
• Total tweets analyzed - 9650 
• Accuracy - 99% 
• Neutral Tweets - 42% 
United 
Kingdom 
23% 
Germany 
3% 
India 
5% 
France 
5% 
© 2014 18 Impetus Technologies 
Sentiments: Nokia Lumia 
42% 
11% 
11% 
Recorded version available at 
United 
States 
35% 
http://www.impetus.com/webinar_registration?event=archived&eid=58 
Indonesia 
15% 
Italy 
8% 
Mexico 
3% 
Turkey 
2% 
Canada 
1% 
Demographics by –ve sentiment 
3% 54% 
1% 
Positive 
Tweets 
Negative 
Tweets 
7% 
8% 
9% 
11% 11% 10% 
11% 
11% 
United 
States 
United 
Kingdom 
Indonesia 
Italy 
France 
India 
Demographics by +ve sentiment
Case study : Nokia 
• Successful online campaign for Nokia 
© 2014 19 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58 
• Lumia 
• Pureview 
• Nokia CRM @nokia (Official Channel) had 
positive mentions tweets 
• Reputation very high for all Hashtags of 
#nokia, #lumia, #pureview 
• Brand management measured via custom 
keywords search for nokia with no hash tags 
- mentions with mostly positive sentiment 
Reputation 
Management 
Brand 
Management 
CRM
Case study : iPad 3 
• Search keyword “ipad3” 
• Total FB status analyzed : 3200 
• Accuracy: 97% 
• Neutral FB Status: 53% 
Demographics: -ve Sentiment 
© 2014 20 Impetus Technologies 
Sentiments: Apple’s iPad3 
Positive Negative Neutral FP 
Recorded version available at 
48% 
53% 
+ve Sentiment 
United States Germany 
France Mexico 
http://www.impetus.com/webinar_registration?event=archived&eid=58 
6% 
8% 
2% 
36% 
United States Germany France Mexico Canada 
31% 
13% 
3% 
23% 
3% 
4% 
1% 
17% 
52%
Case Study : iPad 3 
Overall Apple’s performance on online 
campaign was effective 
© 2014 21 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58 
• Product: iPad3 
Sentiment: Positive 
• General brand perspective is positive 
• CRM – Existing customers feel positive 
Reputation 
Management 
Brand 
Management 
CRM
What It Looks Like? 
© 2014 22 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
Summing Up 
• Traditional Approach – NLP and Artificial Intelligence 
• We recommend - A Sentiment Analytics solution based on Machine 
Learning, n-gram and Bayes filter classification 
• Addresses neutral social media mentions, sentiment override, target 
overlook actual verbatim 
• Ability to cross-reference intensity, influence trajectory, velocity and 
sentiment of each social media mention 
© 2014 23 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
© 2014 24 Impetus Technologies 
About Impetus
• Strategic partners for software product engineering and 
R&D 
• Thought leaders in cutting-edge technologies 
• Mature processes and practices that are methodical, yet 
flexible 
• Diverse domain expertise 
© 2014 25 Impetus Technologies 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58
© 2014 26 Impetus Technologies 
Q & A
© 2014 27 Impetus Technologies 
Thank You 
Write to us at inquiry@impetus.com 
Follow us on Twitter @impetustech 
Recorded version available at 
http://www.impetus.com/webinar_registration?event=archived&eid=58

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SAP Build Work Zone - Overview L2-L3.pptx
 

Building a Sentiment Analytics Solution powered by Machine Learning- Impetus Webinar

  • 1. Impetus Technologies Inc. Building a Sentiment Analytics Solution Powered by Machine © 2014 1 Impetus Technologies Learning Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 2. Outline • Sentiment Analysis – Why? • Solution landscape • Addressing challenges with Machine Learning • Building a sentiment analytics solution – Leveraging Machine learning and n-gram • Case Studies © 2014 2 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 3. Sentiment Analysis • Determines the attitude of a speaker or a writer with respect to a particular subject, event or campaign • Computational study of opinions, sentiments, and emotions expressed in text © 2014 3 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 4. Measuring Sentiments © 2014 4 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 5. Current Solutions Landscape • Natural Language Processing – Deals with the actual text element – Transforms text into a format usable by machine • Artificial intelligence – Uses information by NLP and Mathematical calculations – Determines negative, positive or neutral sentiments – Used for clustering © 2014 5 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 6. Sentiment Analysis: Challenges • Demystifying accuracy • Inability of machines to gauge and measure sentiments accurately • Isolating content types • Neutral nature of social media mentions • Sentiment override • User needs override control due to inaccuracy of automated sentiment measurement © 2014 6 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 7. Machine Learning Intelligent structure that acquires and integrates Learns from experience, training, analytical observation © 2014 7 Impetus Technologies knowledge automatically Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 8. Subjectivity Vs Sentiment Sentiment analysis - text classification problem • Segregate • Opinionated documents as per positive/ negative • Sentence or a clause of the sentence as subjective or objective • Subjective sentence or clause on the basis of positive, negative or neutral © 2014 8 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 9. Determining Polarity Leveraging Machine Learning Algorithm identifies positive/ negative/neutral sentiments Refers knowledge bank to determine polarity of a new sentence or word A knowledge bank is the database of pre-trained words and sentences classified © 2014 9 Impetus Technologies as negative, neutral, positive Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 10. Predicting Sentiment Intensity • Benchmark neutral - say 40-50% of positive is neutral – Intensity below the benchmark is negative and above is positive. • Referring Knowledge Bank – Continuously trained by a Machine Learning Algorithm – Intensity predictions becomes accurate Occurrence of a word or sequence of words in a particular polarity decides the © 2014 10 Impetus Technologies intensity of the overall sentiment Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 11. How it works? © 2014 11 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 12. Text classification –n- gram © 2014 12 Impetus Technologies Result Report Ex: RUBBISH – Negative RUBBISHING – Negative RUBBISHED - Negative Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 13. Building Knowledge Base © 2014 13 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 14. Leveraging Machine Learning © 2014 14 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 15. Impetus Solution • Intuitively retrieves input text for analysis • Processes various Low level APIs, REST APIs, enriched XML DOC, Text, © 2014 15 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58 or RSS • Architecture enables exporting services in form of REST APIs • Intuitive solution, capable of processing near real-time data using Big Data stack • Concurrent processing system enables fast results with higher accuracy
  • 16. What’s new? Higher accuracy Identifies influencers Reputation as per demographics Measuring sentiment intensity © 2014 16 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 17. Case Studies Nokia Lumia (On Twitter) Apple’s iPad3 (On Facebook) © 2014 17 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 18. Case study : Nokia • Search keyword - “Nokia Lumia” • Total tweets analyzed - 9650 • Accuracy - 99% • Neutral Tweets - 42% United Kingdom 23% Germany 3% India 5% France 5% © 2014 18 Impetus Technologies Sentiments: Nokia Lumia 42% 11% 11% Recorded version available at United States 35% http://www.impetus.com/webinar_registration?event=archived&eid=58 Indonesia 15% Italy 8% Mexico 3% Turkey 2% Canada 1% Demographics by –ve sentiment 3% 54% 1% Positive Tweets Negative Tweets 7% 8% 9% 11% 11% 10% 11% 11% United States United Kingdom Indonesia Italy France India Demographics by +ve sentiment
  • 19. Case study : Nokia • Successful online campaign for Nokia © 2014 19 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58 • Lumia • Pureview • Nokia CRM @nokia (Official Channel) had positive mentions tweets • Reputation very high for all Hashtags of #nokia, #lumia, #pureview • Brand management measured via custom keywords search for nokia with no hash tags - mentions with mostly positive sentiment Reputation Management Brand Management CRM
  • 20. Case study : iPad 3 • Search keyword “ipad3” • Total FB status analyzed : 3200 • Accuracy: 97% • Neutral FB Status: 53% Demographics: -ve Sentiment © 2014 20 Impetus Technologies Sentiments: Apple’s iPad3 Positive Negative Neutral FP Recorded version available at 48% 53% +ve Sentiment United States Germany France Mexico http://www.impetus.com/webinar_registration?event=archived&eid=58 6% 8% 2% 36% United States Germany France Mexico Canada 31% 13% 3% 23% 3% 4% 1% 17% 52%
  • 21. Case Study : iPad 3 Overall Apple’s performance on online campaign was effective © 2014 21 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58 • Product: iPad3 Sentiment: Positive • General brand perspective is positive • CRM – Existing customers feel positive Reputation Management Brand Management CRM
  • 22. What It Looks Like? © 2014 22 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 23. Summing Up • Traditional Approach – NLP and Artificial Intelligence • We recommend - A Sentiment Analytics solution based on Machine Learning, n-gram and Bayes filter classification • Addresses neutral social media mentions, sentiment override, target overlook actual verbatim • Ability to cross-reference intensity, influence trajectory, velocity and sentiment of each social media mention © 2014 23 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 24. © 2014 24 Impetus Technologies About Impetus
  • 25. • Strategic partners for software product engineering and R&D • Thought leaders in cutting-edge technologies • Mature processes and practices that are methodical, yet flexible • Diverse domain expertise © 2014 25 Impetus Technologies Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58
  • 26. © 2014 26 Impetus Technologies Q & A
  • 27. © 2014 27 Impetus Technologies Thank You Write to us at inquiry@impetus.com Follow us on Twitter @impetustech Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=58