Latent Semantic Analysis (LSA) is an advanced form of statistical language modeling that cuts through the noise to expose contextual meaning, and is a key feature of Oracle Social Relationship Management platform. Come and learn how LSA delivers more accurate,contextualized, precise and relevant insights. Oracle SRM listening capabilities go well beyond keyword and Boolean searches to reveal insights like consumer intent, political intent, product likes/dislikes, and customer service issues.

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How to use Latent Semantic
Analysis to Glean Real Insight
Better insights, Better content, Better engagement
Franco Amalfi
Director, Digital Engagement Strategy Program
Oracle Public Sector North America
23 May 2015

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Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, and timing of any features or
functionality described for Oracle’s products remains at the sole discretion of Oracle.
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Delivering Service to Citizens is Changing
Oracle Confidential
1980s 1990s 2000s 2010s
Empowered
Employees
Digital is
Humanized
Knowledge
Everywhere
Internet of
Things
Mobile as
Primary Channel
Cross-Channel
Service
WHAT’S NEXT
what’s
CHANGED
4

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Empowered Citizens
5
Always Connected, Always Sharing, Always Aware
COMMUNICATION HAS CHANGED
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Social is a Key Component of a Citizen Engagement Strategy
Public Opinion
Understand sentiment on key issues
on an ongoing basis
Citizen Engagement
Interact with constituents on social
networks to reach them rapidly and
at a lower cost
Transparency & Collaboration
Connect with constituents on key
issues to better gauge needs and
align strategy
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Average Time Spent
on Social Media:
2.1 Hours
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Challenges in the Modern Social Environment
Finding right communication channels 4
Citizens in multiple channels 2
Citizens posting problems publicly 3
Too much noise in social media 1
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Oracle Social Relationship Management
Internal Social
Collaboration
Social Engagement
and Listening
Social
Data
Social Publishing
Better Insights, Better Content, Faster Service
Leverage Oracle Social to empower
your agency, enhance your CX
capabilities and grow your business.
A unified social solution providing best-
in-class networking, listening,
engagement and publishing that can
socially enable the enterprise.
Set of prebuilt integrations for social
listening and engagement, social
marketing, social commerce, social selling
and social customer service.
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Typical Social Listening Challenges
Spam and duplicate posts1
Large conversation volumes3
Search term ambiguity2
Finding value in posts4
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Oracle Uses a Blended Technology Approach for Listening
Unstructured Text Processing
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Latent
Semantic
Analysis
Natural
Language
Processing
Keyword
Boolean
Terms plus Match Any,
Match All, Match None
conditions
Parsing unstructured text to
diagram speech
Used in setting up Topics through
Themes, and in categorization to:
Topics & Indicators

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Blended Listening Technology Approach
Comparison
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0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Keyword Only Keyword Boolean KB & Semantic
Context
Noise
Missed Valid
Valid
• Keyword Only
overstates by 800%
• Keyword Boolean
misses 40%
• Semantic Search –
achieves most valid
content

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What I want to get posts about What I will get posts about in a keyword
solution
13
Example: Search Social Media for ‘Jaguar’
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Keyword Solutions Use Boolean Logic to Try to Find
Relevant Posts
AND
(car OR drive OR driving OR automobile OR buy OR
buying OR bought OR purchase OR purchasing OR
purchased OR dealer OR dealership OR cars OR want
OR …)
NOT
(football OR jacksonville OR stadium OR team OR
animal OR jungle OR zoo OR lions OR tigers OR bears
OR dating OR coach OR player OR players OR …)
JAGUAR
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PROS CONS
15
Keyword Solution Using Boolean Search Pros & Cons
+ Tends to return results quickly
+ Quick on-boarding process
- Topics time consuming to build
- Must read results to find irrelevant posts
- No advanced analytics unless outsourced to 3rd
party
- Time consuming & no consistency
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A data dictionary is built to increase
accuracy
Common Advanced Analytics – Term
Clouds
16
How Natural Language Processing is Better than Keyword
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When all these things… … Mean this:
17
What Natural Language Processing Has Difficulty
Determining
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Doctor
Physician Pediatrician
Surgeon
General
Practitioner

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PROS CONS
18
Natural Language Processing Pros & Cons
+ More relevant results
+ Advanced analytics via term clouds
+ More accurate sentiment
- Slow processing speeds
- Lengthy on-boarding time (months vs. days)
- Doesn’t automatically know when multiple words
have same meaning
- Time consuming & expensive
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How Does Latent
Semantic Analysis
Work?
Uses a statistically based algorithm that
automatically groups conversations
together that look alike.
Or more simply put…
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Occurrence
Matrix
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Processed Jaguar
Conversations
Jaguar
post
Jaguar
post
Jaguar
post
Jaguar
post
Jaguar
post
Jaguar
post
Jaguar
Cars
Drive
Buy /
loan
Jungle
Animals
Hunt
Football
Soccer
Game
Jaguar
Cars
Drive
Buy /
loan
Jungle
Animals
Hunt
Football
Soccer
Game
Jaguar
Cars
Drive
Buy /
loan
Jungle
Animals
Hunt
Football
Soccer
Game
Jaguar
Sedan
Buick
Mustang
VehicleCoup
Wheel
Jaguar
Cars

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LSA Technology
Finding & Targeting
the right
conversations in all
the noise
92% Accurate
Categorization

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LSA Snippets only show relevant
text around target word
Advantage =
1. More accurate sentiment
2. Thematic analysis
3. Indicators
4. Categorization

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PROS CONS
24
Latent Semantic Analysis Pros & Cons
+ Automatic categorization
+ 92% accurate categorization
+ Advanced analytics via themes & term clouds
+ White space analysis
+ Indicators for insight discovery
+ More accurate sentiment
+ Fast processing speeds
+ Easy on-boarding process
- None
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Summary Snapshot Comparison
Capability Keyword / Boolean Natural Language Processing Latent Semantic Analysis
Rapid set-up of listening topics 4 2 4
Listening accuracy; ease of
removing irrelevant results
1 3 4
Sentiment analysis without manual
effort
0 1 3
Indicators 0 0 4
Advanced analytics 0 4 4
Speed of run-time execution 4 2 4
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Best Results Are Achieved When You Use All Three
Oracle SRM Does
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Blended Technology Approach
High categorization
accuracy92% Reduced cost
1 Set up a topic with a single
keyword
Faster time to insight
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Better Results and Ease of Use

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DEMO
Latent Semantic Analysis in Action
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Contact Us
Franco Amalfi
Email: franco.amalfi@oracle.com
@amalfifranco
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https://www.linkedin.com/in/francoamalfi