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Stuart Shulman

Tecnología Empresariales

The Value Proposition
Our solution helps users easily discover information to:
• streamline business processes
• increase ROI & create new business opportunities
• identify positive and negative trends
• discover unique, rare or unexpected information

The Core Methods
Coding and Classifying Text Data

Iteration and Re-Use Are Critical Techniques

Measure Everything Starting With Human Agreement

“CoderRank” – A LifetimeAccuracy Measurement
Vision Critical Patent Pending – “Enhanced Machine Learning”

Five Essential Tools for TextAnalytics
1. Search
2. Filtering on Metadata
3. Human Coding
4. Automated Clustering
5. Machine Classification

A Social Media Use Case
Sifting and Sorting Relevant Data

Great Researchers Demand Transparent Tools

Fair Warning
This part of the presentation contains strong and
potentially quite
offensive, inappropriate, disturbing, or just
completely stupid language.

Create Custom Machine Classifiers
Yes
No
No

Search is Fundamental for Purposive Sampling

Tumblr. – “The Wild West of the Internet”

Stupid Stuff People Do & Tweet
redacted
redacted

Are These Tweets Just Social Garbage?
redacted
redacted

Signs of Health Fear Engagement
redacted
redacted

An IdeaScreen Use Case
Concept Testing Data

Near Duplicate Clusters Can Be Interesting

Two Naturally Occurring Clusters of Free Text

Wherever Humans Go in Numbers, There Are Clusters

A„Simple‟ Coding Scheme with No Coder Training

Testing Coder Agreement on a Small Sample

TextAnalytics is a Series Buckets & Datasets

A New Vision Critical Front End
The First Preview of the New Release

Leverage Item Metadata While Coding or Filtering

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Summit slide loop ny

1. Introduction to Text Analytics October 2, 2013 Dr. Stuart Shulman Phone No.: +1-413-345-8939 E-mail: stu.shulman@visioncritical.com

2. The Value Proposition Our solution helps users easily discover information to: • streamline business processes • increase ROI & create new business opportunities • identify positive and negative trends • discover unique, rare or unexpected information

3. How Do These Tools Help Analysts?

4. What This Means forAnalysis

5. The Core Methods Coding and Classifying Text Data

6. Iteration and Re-Use Are Critical Techniques

7. Measure Everything Starting With Human Agreement

8. The Core DiscoverTextApproach

9. An Indispensable Role for Humans

10. Innovation Happens in Groups

11. “CoderRank” – A LifetimeAccuracy Measurement Vision Critical Patent Pending – “Enhanced Machine Learning”

12. Five Essential Tools for TextAnalytics 1. Search 2. Filtering on Metadata 3. Human Coding 4. Automated Clustering 5. Machine Classification

13. A Social Media Use Case Sifting and Sorting Relevant Data

14. Great Researchers Demand Transparent Tools

15. The HMC is a Leading Edge Gnip Customer

16. Gnip Data Streams and Search Filters

17. Fair Warning This part of the presentation contains strong and potentially quite offensive, inappropriate, disturbing, or just completely stupid language.

18. Studying Media Campaign Effects

19. Create Custom Machine Classifiers Yes No No

20. Search is Fundamental for Purposive Sampling

21. Defined Search Speeds Up Discovery

22. Tumblr. – “The Wild West of the Internet”

23. Stupid Stuff People Do & Tweet redacted redacted

24. Are These Tweets Just Social Garbage? redacted redacted

25. Signs of Health Fear Engagement redacted redacted

26. An IdeaScreen Use Case Concept Testing Data

27. Raw VoC Data: AFortune 500 Tech Company

28. Near Duplicate Clusters Can Be Interesting

29. Two Naturally Occurring Clusters of Free Text