1. Feelings quantified – scoring and storing social media sentiment
Matt Gordon

2. Speaker info Matt Gordon Architect Matt.Gordon@insight.com

3. Speaker info Matt Gordon Co-Founder FGE Professional Sports Analytics

4. About ME 15+ years of SQL Server experience
Microsoft Data Platform MVP
IDERA ACE
Managed 24x7 datacenters
Worked on development teams
MCSE: Data Management and Analytics
PASS Summit 2017 and 2018 speaker
Leader of Lexington, KY PASS Local Group

5. How I picked my twitter handle and domain name

6. agenda What is sentiment analysis?
Why is sentiment analysis important?
How did I get involved in this?
What did I build? (English Premier League Mood Table)
How did I build it?
Wrap-up and takeaways
Q&A
Takeaway 1: Logic Apps are really powerful (mention training and discount code here) and Cognitive Services are cool as well
Takeaway 2: There are things we can do with data outside of our job roles that add value to our company

7. What is sentiment analysis?
“The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer’s attitude towards a particular topic, product, etc., is positive, negative, or neutral.”
Google’s definition
“Using computer magic to figure out how people are feeling when they tweet about something.”
My definition

8. What is sentiment analysis?
Also known as opinion mining
Concept has been around for a while but rise of social media brought it to the forefront
Typically done with specialized tools whose algorithms are unknown
Azure Cognitive Services API democratizes this to an extent

9. What is sentiment analysis?
What are the Cognitive Services APIs?
Sets of machine learning algorithms to solve problems in the field of AI
These algorithms can be consumed through standard REST calls over the Internet
Comprehensive documentation can be found here:

10. What is sentiment analysis?
List of Cognitive Services APIs
Vision (analyze images and videos)
Speech (speech recognition and speaker identification)
Language (understand sentences and intent)
Knowledge (enhanced search for research)
Search (applies ML to web searches)
Mood table (and similar sentiment analysis) uses Text Analytics API of Language API

11. Why is sentiment analysis important?
News cycles used to last days – now they last hours
Users/customers live on social media these days
Political divisions can affect and “enhance” people’s outrage
Being on the wrong end of an unfortunate tweet or post can have lasting consequences
Companies should baseline their social media sentiment

12. Why is sentiment analysis important?
Dove Body Wash Facebook campaign in October 2017
Took the brand nearly two days to offer a thorough response
Proper sentiment analysis would have alerted them to the issue much earlier
Response “by feel” is not fast enough

13. Why is sentiment analysis important?
Entenmann’s #NotGuilty tweet in July 2011
Tweeted on a hashtag dedicated to Casey Anthony verdict
Didn’t respond to negative attention for hours
Account was actually deleted for a period of time

14. Why is sentiment analysis important?
#MyMcDonaldsStory
Brands can unintentionally create issues for themselves
Important to monitor campaigns where feedback has been solicited
Have contingency plans for how to manage that content
Delete tweets?
Participate in campaign?
Monitor sentiment

15. How did I get involved in this?

16. How did I get involved in this?

17. How did I get involved in this?
Men In Blazers (Roger Bennett and Michael Davies)
Popular soccer podcast
TV show on NBC Sports Network
Podcast in mid-October 2017 musing about a “mood table”
Contacted them with a POC and it’s now become a regular feature on the podcast

18. How did I get involved in this?

19. How did I get involved in this?
Brad Ball’s sentiment analysis blog got my train of thought started
@sqlballs on Twitter, is his blog
Premier League Mood Table expands on single-event sentiment
Ranks clubs by supporter sentiments within 10 minutes of the final whistle of a match

20. What did I build? Premier League Mood Table Azure SQL DB
Logic app for all 20 clubs
Text Analytics API of Cognitive Services Language API
Azure Scheduler Job Collection*

21. What did I build?

22. What did I build?

23. How did I build it? Azure SQL DB
Created database and table to store Twitter information
Sentiment score, account, location, tweet text, etc.
Queries to rank the clubs by sentiment from best to worst
1 is most positive
0 is most negative
0.5 is no sentiment detected

24. How did I build it? Logic Apps
Logic apps are a cloud service that helps you automate and orchestrate tasks, business processes, and workflows
One per club
“When a new tweet is posted” trigger
Feeds tweet text to Detect Sentiment action from Text Analytics API
Final step is Insert Row action into Azure SQL DB
Original version also streamed to Power BI

25. How did I build it? Azure Scheduler Job Collection
Uses Azure AD to authenticate the logic apps
Direct scheduling interface for enable and disable actions
Provides run history
Provides execution count and error count
Helps manage costs
*Will be deprecated on September 30, 2019
Recurrence trigger new scheduling method after that date

26. DEMO TIME
Mood Table In-depth

27. How did I build it? AWS Can Do This Too! Amazon RDS for database
Amazon Comprehend for text and sentiment analysis
Amazon Lambda or StepFunctions for logic app-like behavior
CloudWatch Events can provide scheduling

28. WHERE ELSE CAN WE APPLY this technology?
Transfer data between two disparate systems
Healthcare
Sentiment analysis on knowledge base/community posts
Sentiment analysis on monitored social media
School violence
Self-harm

29. What’s next? (soccer customer things)
Using Python and/or rtweet to scrape past tweets (and ML to score those tweets) in order to form more cohesive and customizable sentiment pictures
Working with soccer clubs to map this against fan response, souvenir sales, and game action
Working with Raspberry Pi and microphone arrays to do in-stadium “sentiment”

30. What’s next? (soccer customer things)
Event monitoring
Custom hashtags or matchday/event experiences
Allows for real-time monitoring of on-site fan sentiment
Enables quick reactions to potential issues

31. What’s next? (non-soccer customer things)
Azure function to send an or initiate a workflow alerting about Tweets below a certain sentiment score
Power BI live sentiment dashboard
PASS Summit demo video here
Geography-based reports

32. THE SLIDE WHERE I SHILL FOR TRAINING I MADE
In-depth Logic Apps course with Cognitive Services labs
Click “Buy Now” button
In cart, click “I have a discount coupon” and then enter code MattGordon
20% off any of their on-demand training courses and my wife will be impressed that people keep buying something I made

33. Wrap-up and takeaways
Social media presence requires sentiment analysis
Any data professional or data-curious pro can have a role in this, especially in smaller organizations
Underscores how important machine learning is to understand
Language API (particularly Text Analytics) and Logic Apps give you powerful tools to measure company or personal brand online
I am a big dork that built something to rank soccer teams based on feelings

34. Questions?

35. Speaker info Matt Gordon Architect Matt.Gordon@insight.com

36. REFERENCes and resources
Cognitive Services Documentation:
Text Analytics overview:
Human Language Technologies white papers from MS:
LUIS white paper from MS Research:
AWS doc on building equivalent in AWS: