Got Chaos? Extracting Business Intelligence from Email with Natural Language Processing and Dynamic Graph Analysis

Got Chaos?
Extracting Business Intelligence from Email
with Natural Language Processing and
Dynamic Graph Analysis

Steve Kramer, Ph.D.
President & Chief Scientist
Paragon Science, Inc.

Copyright © 2013-2014 Paragon Science, Inc. and Digital Reasoning, Inc. All rights reserved.

Matthew Russell
Chief Technology Officer
Digital Reasoning, Inc.

Overview
•  Matthew Russell
•  Intro & Background
•  Data Science @ Digital Reasoning
•  Making Human Language Viable for Data Science

•  Dr. Steve Kramer
•  Intro & Background
•  Data Science @ Paragon Science
•  Dynamic Graph Analysis on the Enron Corpus

2

“Any sufficiently advanced
technology is indistinguishable
from magic.”
--Arthur C. Clarke


3!

3

Hello, My Name Is … Matthew
•  Background in Computer Science
•  Data Mining & Machine Learning
•  CTO @ Digital Reasoning
•  Natural Language Processing
•  Author @ O’Reilly Media
•  Mining the Social Web
•  Fitness junkie
•  CrossFit, triathlon, yoga
•  Twitter, etc.
•  @ptwobrussell

4

•  Flagship Product
•  Synthesys
•  Makes human language viable for data science

•  Customers
•  Now: defense/intel, finance
•  Soon: healthcare & alternative energy

•  Offices
•  Nashville, NYC, DC, & London

5

An “Oracle” for Human Language Data
Government

Legal

Health

Financial

Verticals

Pl a t f o rm
( D a ta O rg a n i z ed &
Application-Ready)

Relational Database
Management System
(RDBMS)

Synthesys
Knowledge Graph Management System
(KGMS)
Enables applications on unstructured data

Enables applications
on structured data

Reason
Resolve
Read

Infrastructure

Processing Platforms and Data Stores

Data Sources
External Data

Internal Data


6

Data Alchemy
•  Data
•  Documents & document fragments

•  Information
•  Assertions, extractions, etc.

•  Knowledge
•  Aggregated information

•  Wisdom
•  “Compressed” knowledge

•  Gold

7

"Knowledge is a process of
piling up facts; wisdom lies in
their simplification.”
--Martin Fischer


10!

10

Natural Language Building Blocks


11

Big Data Needs Big Understanding


12

The End State: A Knowledge Graph
Fund

SpotTail
Capital Advisors

Stan
Druckenmiller
Paul
Tudor Jones

Fantasy Football
League

Goldman
Sachs
Voyager Capital
Partners

Raj Rajaratnam

Proctor &
Gamble
P & G Board

David
Loeb

Lunch

Rajat Gupta

McKinsey
& Co.

Galleon
Group LLC

Richard
SchuHe

Gary
Cohn

GS
TransacDons
PorNolio
Manager

Anil Kumar

Intel Corp.

Rajiv Goel

Wharton
School

Galleon
Kris
Tech
Chellam
Fund

Krish
Panu

Leon
Shaulov

Ian
Michael
Horowitz Cardillo

P&G
TransacDons

1. READ: Forge natural language building blocks & build an information graph
2. RESOLVE: Introduce hierarchy & compress the information graph into knowledge
3. REASON: Exploit the knowledge to solve business problems

13

“In God we trust.
All others must bring data.”
--W. Edwards Deming


14

Overview of Enron
•  A Texas-based energy company that grew to a
multibillion-dollar company between 1985 and 2001
•  The substance of the Enron scandal involved the use of
financial instruments called raptors to effectively hide
accounting losses.
•  Soon after the scandal was revealed in 2001, Enron filed
bankruptcy to the tune of over $60 billion dollars
•  The largest bankruptcy in U.S. history (at the time)!


15

Could It Have Been Prevented?
•  Maybe/Probably – Steve will share some insights
•  The answers were hiding in plain sight
•  Fast-forward till now…
•  Any enterprise has significant potential liability lurking in
digital forms of human language data
•  “Deep” NLP can power applications to help thwart
these types of situations and do significant moral good


16

Now Introducing…
Dr. Steve Kramer
<Applause />


17

Hello, My Name Is … Steve
•  Computational Physicist
•  Nonlinear Dynamics and Chaos
•  Dynamic Graph Analysis

•  Data Science Entrepreneur
•  Paragon Science, Inc.

•  Group Fitness Instructor
•  BODYPUMP
•  BODYATTACK
•  CXWORX

•  Food and Wine Aficionado
•  Twitter, etc.
•  @ParagonSci_Inc
•  @dr_steve_kramer

18

Extracting Critical Business Intelligence from Data Streams
•  Digital Reasoning’s Synthesys platform for natural language
processing
•  Paragon Science’s dynamic anomaly detection software
•  Business goals:
•  Help seize opportunities
•  Mitigate risks
•  Case study: Enron email data set
•  Identify key individuals by position in network
•  Highlight unusual changes in sentiments
•  Drill down to relevant source messages


19

Example: Enhanced Enron Email Data Set
from Digital Reasoning
•  Graphml representation for each email message
•  343,134 email messages
•  28,905 email addresses
•  Natural language processing artifacts
•  Messages
•  Sentences
•  Phrases
•  Tokens
•  Co-references
•  Co-reference chains

Copyright © 2013-2014 Paragon Science, Inc. and DigitalParagon Science, Inc. reserved.
Reasoning, Inc. All rights
20

20

Paragon Science Enron Network Analysis
Ingest Digital Reasoning Data
Construct
Graph for Each
Day

Find Key Individuals with
K-Core Decomposition

Perform Sentiment Analysis
on Messages
Apply Dynamic
Network
Analysis
Identify Anomalous Clusters
and Time Periods
Relate Anomalies to Source Data
21

21

K-Core Decomposition of the Enron Network

The users at the
center are bestpositioned to
spread information
and influence the
network.
J.I. Alvarez-Hamelin, Alain Barrat, Alessandro Vespignani,
Luca Dall'Asta, and Mariano Beiró http://lanet-vi.fi.uba.ar/
22

22

K-Core Decomposition: Central Core

23

23

Focus Users for Sentiment Analysis
a..howard@enron.com
a..shankman@enron.com
chris.germany@enron.com
d..steffes@enron.com
darron.giron@enron.com
debra.perlingiere@enron.com
elizabeth.sager@enron.com
enron.announcements@enron.com
gerald.nemec@enron.com
jeff.dasovich@enron.com
jeff.skilling@enron.com
jeffrey.hodge@enron.com
jeffrey.shankman@enron.com
john.arnold@enron.com
kam.keiser@enron.com
kate.symes@enron.com
kay.mann@enron.com

24

kimberly.watson@enron.com
leslie.hansen@enron.com
leslie.lawner@enron.com
louise.kitchen@enron.com
m..love@enron.com
mark.haedicke@enron.com
mark.taylor@enron.com
michelle.cash@enron.com
nmann@erac.com
richard.sanders@enron.com
richard.shapiro@enron.com
rod.haysleH@enron.com
sally.beck@enron.com
sara.shackleton@enron.com
steven.kean@enron.com
susan.scoH@enron.com
tana.jones@enron.com
tracy.geaccone@enron.com
vince.kaminski@enron.com

24

Enron Data Enhanced by NLP and Sentiment Analysis
•  For the central individuals in the Enron network, we construct
dynamic networks using the phrases extracted from the
emails by Digital Reasoning.
•  Use the LIWC (Linguistic Inquiry and Word Count) tool to
classify the sentiment scores of the phrases.
•  Prof. James Pennebaker from UT Austin (http://
www.liwc.net/)
•  Sample categories
•  Positive emotion
•  Negative emotion
•  Anger
•  Anxiety
25

25

High-level Sentiment Analysis Results

26

26

Positive Emotion Weight Totals

Peak on Feb. 28, 2001 for

27

27

Anxiety Weight Totals

Peak on Feb. 28, 2001 for

28

28

Related Message from Feb. 28, 2001
Message-ID: <8261377.1075848143751.JavaMail.evans@thyme>Date: Wed, 28 Feb 2001 06:19:00 -0800
(PST)From: steven.kean@enron.com
To: bernadette.hawkins@enron.com
Subject: Energy Issues …
Forwarded by Steven J Kean/NA/Enron on 02/28/2001 02:19 PM ----To: Ann M Schmidt/Corp/Enron@ENRON, Bryan Seyfried/LON/ECT@ECT, dcasse@whwg.com, Riverside
Press 2/23: "Power line plan has new foes"Contra Costa Times, 2/23: "GOP in a fix over power crisis"Sac
Bee, Fri 2/23: "Davis says State has tentative deal for Edison grid"SF Chron 2/23: "Utilities Search for
Long-Term Fix During Breather...
GOP in a fix over power crisis
Leaders seek solutions that won't undercut past support for deregulation
By Daniel Borenstein
TIMES POLITICAL EDITOR
California Republican Party leaders are trying desperately to politicize the
state's electricity crisis by blaming Gray Davis, but it seems that the
harder they try the more popular the Democratic governor becomes.
The latest GOP push will come today when party leaders, meeting in Sacramento
for the start of their three-day state convention, hold a hastily organized
workshop on energy.
"We should be explaining to California that Gray Davis was asleep at the
switch last year," said one of the scheduled speakers, Republican strategist
Dan Schnur. "But that message can only work if it's coupled with a proposal
for an alternative solution."

29

29

Apply Paragon Science Dynamic Anomaly Detection

•  Simple measures such as counts can miss important features
•  Use dynamic network analysis to study the changes over time
in:
•  Who communicates with whom
•  The distribution of the emotion-laden phrases in the sent
emails
•  Extract business intelligence

30

30

Dynamic Cluster Analysis
•  Which entities behave or
evolve differently than others
in the data set?

•  Which entities have shifted
their behavior unexpectedly?

31

31

Dynamic Anomaly Detection Overview

•  A general approach that incorporates nonlinear time series
analysis methods
•  Complexity measures
•  Finite-time Lyapunov exponents (FTLEs)
•  Input data
•  Communications or transactional data streams
•  General time-dependent data sets
•  Key questions
•  Which entities behave or evolve differently than others in
the data set?
•  Which entities have shifted their behavior unexpectedly?
32

32

Finite-Time Lyapunov Exponents (FTLEs)
•  General dynamical system

•  Flow map
•  Advects points in the state
space
•  Describes the time evolution
of the system


33

33

Finite-Time Lyapunov Exponents (FTLEs)
•  FTLEs characterize the amount of stretching or contraction
about a point x0 during a time interval T
•  Stability
•  Predictability
•  Definition

34

34

Derived Jacobian Vectors
•  Similarly, characteristic vectors derived from the flow map’s
Jacobian can describe the generalized directions of the local
stretching or contraction.

•  Possible derivation approaches:
•  Weight-based column sampling
•  Singular value decomposition (SVD)
•  Principal component analysis (PCA)

35

35

Paragon Dynamic Anomaly Detection
Representation
of Data at t=ti

Yes

Clustering /
Segmentation

Cluster
Resolution

Feature Vector
Encoding

Outlier Detection
at t=ti

More Time
Intervals?
No

Nonlinear Time Series Analysis
FTLEs, Dynamic Thresholds, etc.

Dynamic Anomaly Detection

36

Pattern
Classification

Outlier
Detection

Domain-Specific Filtering
Threat Signatures,
Risk Profiles, etc.
36

Summary of Top 100 Anxiety Anomalies
Sender

Peak End Date Max Change
Metric
2001-‐05-‐04
3.018

# Anomalies


Peak Start
Date
2000-‐03-‐17


1999-‐12-‐24

2001-‐06-‐08

2.356

34

kay.mann@enron.com

2000-‐09-‐29

2001-‐12-‐14

2.164

2

sara.shackleton@enron.com

2001-‐05-‐18

2001-‐11-‐16

1.893

6


2000-‐07-‐07

2001-‐08-‐10

1.862

5


2001-‐06-‐15

2001-‐11-‐16

1.789

5

48

Dr. Vince Kaminski
Managing Director for
Research at Enron
37

37

Anomaly Detection Results for Anxiety Phrases

Anomalous period for
during August 2000

38

38

Vince Kaminski’s Anxiety Phrase Network in August 2000

39

39

Related Sentences Ranked by Anxiety Weight
Sentence

Message Date

Anxiety Score

the framework with modern credit risk measurement tools leads to a liquidity risk VAR measure

2000-‐08-‐08 02:34:00 0.9

This event has rapidly establishing itself as the risk management industry ,s most important meeDng point 2000-‐08-‐17 04:22:00

0.7

This event has rapidly establishing itself as the risk management industry's most important meeDng point

2000-‐08-‐17 07:01:00

0.7

system providers this is THE financial risk management event of the year
system providers this is THE financial risk management event of the year
bank liquidity risk can be viewed as a variaDon of credit risk analysis

2000-‐08-‐17 04:22:00 0.6
2000-‐08-‐17 07:01:00 0.6
2000-‐08-‐08 02:34:00 0.6

modeling, validaDon, EVT) Advanced Asset & Liability Management, Corporate/Energy Risk Management

2000-‐08-‐17 04:22:00

0.5

the New Products Designed to Stabilise VolaDlity Energy Credit Risk Management GARP

2000-‐08-‐17 04:22:00

0.5

this ConvenDon will consider include Market Risk (stress tesDng, liquidity, jump diffusion

2000-‐08-‐17 04:22:00

0.5

validaDon, EVT) Advanced Asset & Liability Management, Corporate/Energy Risk Management and the
Insurance & Capital Markets
VolaDlity Energy Credit Risk Management GARP is a not-‐for-‐profit, independent organisaDon of risk
management pracDDoner
modeling, validaDon, EVT) Advanced Asset & Liability Management, Corporate/Energy Risk Management

2000-‐08-‐17 04:22:00

0.5

2000-‐08-‐17 04:22:00

0.5

2000-‐08-‐17 07:01:00

0.5

the New Products Designed to Stabilise VolaDlity Energy Credit Risk Management GARP

2000-‐08-‐17 07:01:00

0.5

this ConvenDon will consider include Market Risk (stress tesDng, liquidity, jump diffusion

2000-‐08-‐17 07:01:00

0.5

validaDon, EVT) Advanced Asset & Liability Management, Corporate/Energy Risk Management and the
Insurance & Capital Markets
VolaDlity Energy Credit Risk Management GARP is a not-‐for-‐profit, independent organisaDon of risk
management pracDDoner

2000-‐08-‐17 07:01:00

0.5

2000-‐08-‐17 07:01:00

0.5

40

40

Related Sentences Ranked by Anxiety Weight
Sentence
any quesDons please do not hesitate to contact me
INVITATION TO SPEAK GARP 2001 The 2nd Annual Risk Management ConvenDon 13th & 14th
February, 2001 ) MarrioH World
Three simultaneous streams address tradiDonal pricing and risk management techniques
any quesDons, please do not hesitate to call me at ext
your risk factor will be reduced by a factor equal the sqrt(5
I have referred him to the "Managing Energy Price Risk" book
any quesDons please do not hesitate to contact me
Three simultaneous streams address tradiDonal pricing and risk management techniques
conﬂicts of schedule, please do not hesitate to contact me
modelling approaches to credit risk.
market risks, has received liHle aHenDon in professional or academic journals
the Global AssociaDon of Risk Professionals, I have great pleasure
you to speak at our 2nd Annual Risk Management ConvenDon ) GARP 2001
we lack desperately technical talent
Energy Risk -‐ Tackling Price VolaDlity, AdapDng VaR, Scenario Modelling and Regulatory
Requirements Vince Kaminski
GARP 2000 reﬂected the key concerns of risk management experts
INVITATION TO SPEAK GARP 2001 The 2nd Annual Risk Management ConvenDon 13(superscript
the Global AssociaDon of Risk Professionals, I have great pleasure
you to speak at our 2(superscript: nd) Annual Risk Management ConvenDon
approaches for measuring these risks for EES deals
EES deals given the uncertainDes in energy consumpDon
a framework allowing to measure a bank's structural liquidity risk
I taking over responsibility for semng-‐up EES Europe's Risk Management acDvity
41

Message Date
Anxiety Score
2000-‐08-‐17 04:22:00 0.4
2000-‐08-‐17 04:22:00 0.4
2000-‐08-‐17 04:22:00
2000-‐08-‐07 01:27:00
2000-‐07-‐28 10:05:00
2000-‐08-‐08 02:29:00
2000-‐08-‐17 07:01:00
2000-‐08-‐17 07:01:00
2000-‐07-‐31 08:46:00
2000-‐08-‐02 01:11:00
2000-‐08-‐08 02:34:00
2000-‐08-‐17 04:22:00
2000-‐08-‐17 04:22:00
2000-‐08-‐07 04:13:00
2000-‐08-‐08 02:39:00
2000-‐08-‐17 07:01:00

0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.3
0.3
0.3
0.3
0.3

2000-‐08-‐17 07:01:00
2000-‐08-‐17 07:01:00
2000-‐08-‐17 07:01:00
2000-‐08-‐17 07:01:00
2000-‐07-‐26 02:08:00
2000-‐07-‐26 02:08:00
2000-‐08-‐11 00:42:00
2000-‐08-‐08 02:34:00
2000-‐08-‐03 08:51:00

0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
41

Vince Kaminski’s Anxiety Sentences Network in August 2000

42

42

Vince Kaminski’s Anxiety Sentences Network (Detail)

43

43

Vince Kaminski’s Anxiety Sentences Network:
Gephi Highlights

44

44

Related Messages Ranked by Anxiety Weight
Sender

Source File
./part-‐m-‐00042.base64.stemmed/2369.txt

Anxiety Weight
1



1



0.8333



0.5



0.5



0.5



0.5



0.5



0.5



0.5



0.3333



0.3333

45

45

Top-Ranked Anxiety Message from Aug. 17, 2000
Message-‐ID: <2250375.1075856554294.JavaMail.evans@thyme>
Date: Thu, 17 Aug 2000 08:55:00 -‐0700 (PDT)
From: vince.kaminski@enron.com
To: vkaminski@aol.com
Subject: Re: Cairn Gas Purchase Bid

Douglas S Parsons@ENRON_DEVELOPMENT
08/15/2000 09:30 AM
Source File
To: Doug Leach/HOU/ECT@ECT
./part-m-00042.base64.stemmed/2369.txt
cc: Marc De La Roche/HOU/ECT@ECT

I can appreciate and share your objec`ve. Earlier today I sent a separate
note to Vince forwarding your concerns and asking again for his assistance.
…

To: Douglas S Parsons/ENRON_DEVELOPMENT@ENRON_DEVELOPMENT

I gave you several clear alterna`ves such as contac`ng Vince's structuring
group, Michael Popkin's Southern Cone structuring group and a long discussion
regarding the pricing and suggested "collar." I also asked if you had spoken
to your customer about what they were willing to pay, but that was a non
starter. Trust me, I have seen almost every bad deal Enron has entered into
or afempted to enter into and I am trying to get Metgas to objec`vely
relook at their oﬀer to Cairn become it becomes another bad deal.

46

Anxiety Weight
1

46

Details on Dr. Vince Kaminski

http://www.nytimes.com/2006/01/29/business/businessspecial3/29profiles.html
47

47

Summary of Top 100 Anger Anomalies
Sender

Peak Start Date

Peak End Date

Max Change
Metric

# Anomalies

kay.mann@enron.com

2000-‐08-‐25

2002-‐01-‐04

3.39

47


1999-‐12-‐31

2001-‐06-‐08

2.97

36

chris.germany@enron.com

2000-‐03-‐17

2002-‐01-‐11

2.51

11


2001-‐06-‐15

2001-‐08-‐31

2.37

3


2001-‐07-‐06

2001-‐09-‐21

2.03

3

Kay Mann
Assistant General Counsel
Mark Taylor
VP & Assistant General Counsel
48

48

Anomaly Detection Results for Anger Phrases

Anomalous period for
kay.mann@enron.com
starting in September 2000

49

49

Kay Mann’s Anger Phrase Network (Sept.-Nov. 2000)

50

50

Kay Mann’s Key Anger Sentences
Sentence
we have a fighDng chance
a criDcal point and needs to understand the Nigeria tax implicaDons for the venture

Message Date
2000-‐10-‐21 06:27:00
2000-‐09-‐01 05:05:00

Anger Score
0.4
0.3

the commercial team is now at a criDcal point
he had a heart aHack
5 really bothers her
The Midwest is dominated by verDcally integrated Transmission Providers ("TPs

2000-‐09-‐01 05:05:00
2000-‐10-‐10 02:26:00
2000-‐09-‐18 07:36:00
2000-‐11-‐10 08:56:00

0.3
0.3
0.3
0.3

the Aquarium closed -‐ killed by bike lanes
Assignment language -‐ new language being tortured within the Enron ranks, to GE

2000-‐09-‐14 02:54:00
2000-‐11-‐28 05:20:00

0.3
0.3

my gas won't be cut off this COLD November
such case, you should destroy this message
you tonight to trick or treat
michael cut is toe, I
the criDcal juncture, we should enlist external support

2000-‐11-‐22 02:55:00
2000-‐09-‐01 05:05:00
2000-‐10-‐30 07:45:00
2000-‐10-‐16 06:46:00
2000-‐09-‐15 05:38:00

0.3
0.2
0.2
0.2
0.2

Enron should protest or intervene
Calif., who represents San Diego
State Mkt Structure Blamed For Crisis The hearing
the staff probe, appeared to place much of the blame
I will be leaving around 2:00 for suburban trick or treaDng
Enron should protest or intervene
it screwed up the parking
our criDcal final zoning vote is next Thursday, I
She's not a dumb dog
it just hasn't done the trick
FP&L revealed violaDons

2000-‐11-‐09 01:06:00
2000-‐09-‐12 02:13:00
2000-‐09-‐12 02:13:00
2000-‐09-‐12 02:13:00
2000-‐11-‐09 01:45:00
2000-‐11-‐06 07:34:00
2000-‐09-‐14 06:21:00
2000-‐11-‐01 06:17:00
2000-‐10-‐20 05:32:00
2000-‐10-‐27 01:02:00
2000-‐11-‐10 08:56:00

0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2

51

51

Related Top-Ranked Anger Message #1
Date: Sat, 21 Oct 2000 06:27:00 -‐0700 (PDT)
From: kay.mann@enron.com
To: barbara.gray@enron.com, jeffrey.hodge@enron.com
Subject: Re: Power Plant Development Powerpoint PresentaDon

I don't know if you got this, so here 'Ds. I was out of town and missed the
presentaDon, although I've worked with Herman, Roger and David on these
issues. I'm sure they would be glad to give the presentaDon again for
others with a need to understand the complexiDes of off balance sheet
treatment of power plants.

Kay
…
To: Suzanne Adams/HOU/ECT@ECT
cc: Karen E Jones/HOU/ECT@ECT, Bob Carter/HOU/ECT@ECT, Barton
Clark/HOU/ECT@ECT, Dale Rasmussen/HOU/ECT@ECT, Ed B Hearn III/HOU/ECT@ECT,
maH.maxwell@enron.com, kay.mann@enron.com, Stuart Zisman/HOU/ECT@ECT, Peggy
Banczak/HOU/ECT@ECT, David Leboe/HOU/ECT@ECT
Subject: Re: Power Plant Development Powerpoint PresentaDon

Could you check with David and see if he could fax copies of the PowerPoint
plates to me in Portland so we have a fighDng chance of following along by
tying in by phone? If that is possible, try to send them by Tuesday. Thank
you very much.
Al Larsen

52

52

Date: Fri, 1 Sep 2000 05:05:00 -‐0700 (PDT)
To: kathleen.carnahan@enron.com
Subject: Nigeria Tax Issues

Seyi,

James MacCallon has now ler for Mexico. I am just returning from India and
must step in where he ler oﬀ. I see James has sent a few emails and faxes
to
you but I can ﬁnd no reply from AA although there is a 14-‐July email from you
indicaDng a reply would be sent by 16-‐July. Have you sent a reply and I
have
missed it?

Given that the commercial team is now at a criDcal point and needs to
understand the Nigeria tax implicaDons for the venture and bid, perhaps we
should short-‐cut this Q&A process and have a conference call. I would suggest
early AM Tuesday 20th, what works for you?

53

53

To: Peter J Thompson <peterthompson@akllp.com>
Subject: RE: Weekly GE Conference Call
…
-‐-‐-‐-‐-‐Original Message-‐-‐-‐-‐-‐
From: Kay.Mann@enron.com [mailto:Kay.Mann@enron.com]
Sent: Monday, November 27, 2000 3:14 PM
To: michael.barnas@ps.ge.com; stephen.swir@ps.ge.com;
lee.johnson@ss.ps.ge.com; kent.shoemaker@ae.ge.com;
Lisa.Bills@enron.com; Roseann.Engeldorf@enron.com;
Sheila.Tweed@enron.com; ScoH.Dieball@enron.com; Ben.Jacoby@enron.com
Cc: Suzanne.Adams@enron.com
Subject: Weekly GE Conference Call

Dear Turbine Torture Club Members:

..
Assignment language -‐ new language being tortured within the Enron
ranks,
to GE soon.
Limit of liability, indemnity, etc. -‐ Enron owes GE a posiDon on this.
54

54

Possible Next Steps

•  Sentiment analysis using n-grams
•  Influence calculations: Determine which users were most
effective at spreading the various emotions
•  Topic detection: Perform community detection on the
combined user/phrase networks to determine groups of
users and set of related terms
•  URL phrase analysis: Analyze the dynamics of URL
sharing in the network as an independent indicator of
topics and sentiment

55

55

What Are the Payoffs?

•  Quickly identify key influencers and trends in online networks
with NLP, sentiment analysis, and graph analytics
•  Provide early warning of viral emails, videos, anomalous web
events, or unusual network traffic
•  Enable enhanced business intelligence and proactive
corporate compliance without having to specify normal vs.
abnormal behavior in advance

Copyright ©Science, Inc.
Paragon 2013-2014 Paragon Science, Inc. and Digital Reasoning, Inc. All rights reserved.

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Got Chaos? Extracting Business Intelligence from Email with Natural Language Processing and Dynamic Graph Analysis

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