Invited presentation by Seth Grimes at the 7th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, June 16, 2016

1. An Industry Perspective on
Subjectivity, Sentiment, and
Social
Seth Grimes
Alta Plana Corporation
@sethgrimes
7th Workshop on Computational Approaches to
Subjectivity, Sentiment & Social Media Analysis
June 16, 2016 – San Diego

3. Agenda
Industry applications
… analyst views.
Commercialization illustrated.
Routes to market, futures.

5. Social Media Analytics

6. Brian Solis
http://www.briansolis.com/2012/04/meet-generation-c-the-connected-customer/
A Journey Metaphor

7. Dion Hinchcliffe
https://www.enterpriseirregulars.com/58013/social-media-marketing-predictions-for-2013-part-1/
Subjective Judgments

8. Emotion Discovered

9. Voices

10. http://www.greenbook.org/grit
Research & Insights

11. Current, 33%
Current, 31%
Current, 34%
Current, 47%
Current, 51%
Current, 56%
Current, 47%
Current, 54%
Current, 66%
Expect, 21%
Expect, 24%
Expect, 23%
Expect, 23%
Expect, 28%
Expect, 25%
Expect, 33%
Expect, 28%
Expect, 22%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Events
Semantic annotations
Other entities – phone numbers, part/product
numbers, e-mail & street addresses, etc.
Metadata such as document author, publication
date, title, headers, etc.
Concepts, that is, abstract groups of entities
Named entities – people, companies,
geographic locations, brands, ticker symbols,…
Relationships and/or facts
Sentiment, opinions, attitudes, emotions,
perceptions, intent
Topics and themes
Do you currently need (or expect to need) to
extract or analyze –
http://altaplana.com/TA2014

12. Data Type Examples Applications
Verbatims from
quantitative surveys
Brand trackers,
customer/ employee
engagement studies
Advert/Product testing
likes & dislikes
Enterprise Feedback
Management/Voice of
the customer
programmes
What are people saying?
Auto-coding of verbatim into themes
What is good and bad?
Measure and track sentiment overall and by themes
What should we improve first?
Text based impact/driver analysis for action prioritisation
Real-time analysis of customer feedback
Prioritise actions and interventions in timely fashion
Qualitative surveys
Online communities,
focus group transcripts,
public consultation
transcripts
What is being said and in what context?
Extract key words and patterns in data
Can we map the key themes?
Visualise patterns and relationships between concepts
What should wider analysis focus on?
Guide/focus analysis
Social media data
User Generated
Content from social
networks, data from
forums/ blogs/review
sites, news sites etc...
What are people saying?
Auto-coding of comments into themes
What is good and bad?
Measure and track market sentiment
What is being said about our competitors?
Competitive intelligence
Is there anything new we should be worrying about?
Identify early signals of user/customer opinion
Feedback/data held
by organisations
Call centre
logs/recordings, data
from website, email
data etc..
What have people said in the past?
Audit of existing data
Is any of our existing data
relevant for our current task?
Find relevant data for further analysis
What are people saying?
Identify recurrent themes
https://www.ipsos-
mori.com/researchpublicatio
ns/publications/1766/A-
Guide-to-Text-Analytics.aspx

13. Industry Applications
Market research & customer insights
Customer experience
Social engagement
Brand/reputation management
Recommendation systems
Consumer markets
Financial markets
Health sciences & clinical medicine
Military/intelligence

14. “Emotional Market Research”

15. Decisions
What’s your core capability?
What are your differentiators?
Tool, application, component, or solution?
Industry adaptation, e.g., hospitality, healthcare,
consumer electronics:
• Models.
• Workflow, interfaces, analyses.
NLP/information extraction capabilities.
Data sources handled & data availability.

16. Core?

17. Differentiators?

18. Tool, application, component, or solution?

19. Adaptation

20. NLP/IE

21. http://www.depechemood.eu/DepecheMood.html
Prove It

22. Routes to Market
Academic commercialization office.
Angel, venture funding.
Program funding, for example EU, NSF, IARPA, or
SBIR.
Consulting/services funded.
Alliance with an integrator/consultancy, solution
provider, or customer.
Platform adherence.
Or get hired.

23. Academic +

24. Investors
Consult:
• AngelList (angel.co).
• CrunchBase.
• Index (index.co).

25. Dead

26. Doomed?

27. Platform/
integration

28. Get Hired

29. Sentiment futures
The same, but more so: Descriptive
• Integrated applications.
• Integrated data (behaviors, profiles, reference).
• Personas and affinities.
• Images, audio, and video.
• Physical affective states.
• Cross-source.
New(-er) stuff: Generative
• Conversational interfaces.
• Narrative, argumentation, translation.
• Virtual environments.
Evocative

30. Personas 1

31. Personas 2

32. http://www.beyondverbal.com/#wea
Facial coding demo at: https://labs-
portal.affectiva.com/portal/web-demo
Beyond Text

33. Conversational Interfaces (+ IoT)

34. sentimentsymposium.com
Start-up, government/academic, small company, and
student discounts available.

35. An Industry Perspective on
Subjectivity, Sentiment, and
Social
Seth Grimes
Alta Plana Corporation
@sethgrimes
7th Workshop on Computational Approaches to
Subjectivity, Sentiment & Social Media Analysis
June 16, 2016 – San Diego