PREDOSE:
PRE
SCRIPTION
D
RUG
ABUSE
O
NLINE
-
S
URVEILLANCE
AND
E
PIDEMIOLOGY
Delroy Cameron
9/29/2011
GOAL
To determine user
knowledge
,
attitudes
and
behavior
related to the non
-
medical use of
pharmaceutical
opioids
as discussed on Web
-
based forums
To determine
temporal trends
and
patterns
in
pharmaceutical
opioid
abuse as discussed on
Web
-
based forums
2
P
ROBLEM
Scalability
Data Collection
Flexibility
Data Annotation
Latency of Relevant Information
Reactive Effect
3
A
SPECTS
Information Extraction
Entity Identification/Disambiguation
Relationship Extraction
Triple Extraction
Trend Detection
Spatio
-
Temporal
-
Thematic Analysis
Sentiment Analysis
4
Web
Crawler
Informal Text Database
Web Forums
Machine
Learning
Natural
Language
Processing
2
4
8
Data Cleaning
Stage 1. Data Collection
3
Stage 2. Automatic Coding
Stage 3.
Data Analysis and Interpretation
1
7
Qualitative and Quantitative Analysis
of Drug User Knowledge, Attitudes
and Behaviors
Named Entity Identification,
Relationship Extraction
+
=
Semantic Web Database
Information Extraction Module
Temporal Analysis for Trend Detection
Cuebee
Semantic Web Tools
9
10
Ontology
Triples/RDF Database
Scooner
5
6
Schema
Instances
e.g. Opioid,
Pain Pills
e.g. Suboxone,
Subutex
E
NTITY
D
ISAMBIGUATION
Semantic Similarity
oxy
Oxycontin
OP
Oxycontin
Oxycontin
OC
Oxycontin
OC
oxy
“Experiment
2
:
Fail
-
Grinding
up
and
parachuting
-
despite
milling
these
OPs
down,
they
still
retain
substantial
time
release
.
I
found
this
to
be
a
failure
and
it
released
the
oxy
slowly
over
the
course
of
many
hours
.
oxy
Oxycontin
OP
oxy
Oxycontin
bad boys
Oxycontin
OP
Context
Candidates
6
P
ROBABILISTIC
E
NTITY
D
ISAMBIGUATION
“Experiment 2: Fail
-
Grinding up and parachuting
-
despite milling
these
OPs
down, they still retain substantial time release. I found this
to be a failure and it released the oxy slowly over the course of many
hours
.”
7
Vocabulary
Known Slang/Drug References
Informal Text
Database
Language
Model
NIDA
Erowid
NDCP
DrugSlang
Doc
Bluelight.ru
Opiophile.com
DrugsandBooze.com
Drugbank
Vocabulary
Corpus/Subset
Entity Identification/Disambiguation Architecture
8
S
ENTIMENT
A
NALYSIS
Entities
Oxy, OP
Sentiment Clues
failure, despite
Polarity
“Experiment
2
:
Fail
-
Grinding
up
and
parachuting
-
despite
milling
these
OPs
down,
they
still
retain
substantial
time
release
.
I
found
this
to
be
a
failure
and
it
released
the
oxy
slowly
over
the
course
of
many
hours
.
9
T
EMPORAL
A
NALYSIS
(TIMELIME)
0
100
200
300
400
500
600
700
800
900
2001-09
2003-06
2004-07
2004-11
2005-03
2005-07
2005-11
2006-03
2006-07
2006-11
2007-03
2007-07
2007-11
2008-03
2008-07
2008-11
2009-03
2009-07
2009-11
2010-03
2010-07
2010-11
2011-03
2011-07
Oxycontin (All)
0
100
200
300
400
500
600
2001-09
2003-06
2004-12
2005-04
2005-09
2006-01
2006-05
2006-09
2007-01
2007-05
2007-09
2008-01
2008-05
2008-09
2009-01
2009-05
2009-09
2010-01
2010-05
2010-09
2011-01
2011-05
2011-09
Oxycontin (Bluelight)
0
100
200
300
400
500
600
2005-02
2005-08
2006-01
2006-05
2006-09
2007-01
2007-05
2007-09
2008-01
2008-05
2008-09
2009-01
2009-05
2009-09
2010-01
2010-05
2010-09
2011-01
2011-05
2011-09
Oxycontin (Opiophile)
0
50
100
150
200
250
300
2004-03
2004-10
2005-04
2005-08
2005-12
2006-04
2006-08
2006-12
2007-04
2007-08
2007-12
2008-04
2008-08
2008-12
2009-04
2009-08
2009-12
2010-04
2010-08
2010-12
2011-04
2011-08
Oxycontin (DNB)
10
P
EOPLE
kno.e.sis
Delroy Cameron
Sujan
Udayanga
Amit
P.
Sheth
CITAR
(Center for Interventions, Treatment and
Addictions Research)
Dr. Raminta
Daniulaityte
Dr. Robert Carlson
Russel
Falck
11
Questions
http://wiki.knoesis.org/index.php/PREDOSE
12
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