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Latent semantic analysis and classification modeling in applications for social movement theory
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Latent semantic analysis and classification modeling in applications for social movement theory
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Description
Identifier
Thesis
1996
Author
Spomer, Judith E.
Title
Latent
semantic
analysis
and
classification
modeling
in
applications
for
social
movement
theory
Publisher
Central Connecticut State University
Date of Publication
2009
Resource Type
Master's Thesis
Abstract
Social
Movement
Theory
(SMT)
is
an
area
of
study
in
Sociology
and
Political
Science
that
provides
an
analytical
framework
for
understanding
the
factors
involved
in
organized
social
action
. A
social
movement
develops
in
response
to an
injustice
or
issue
about
which
people
rally
in an
effort
to
solve
the
problem
. In
recent
years
, the
threat
of
terrorism
has
accelerated
research
in
SMT
.
Much
of this
research
has
focused
on
understanding
the
framing
process
,
whereby
a
Social
Movement
Organization
(SMO)
issues
communications
intended
to
influence
perceptions
and
enlist
help
from the
members
of a
community
or
general
population
. The
Internet
has
become
a
primary
medium
for
SMOs
to
distribute
electronic
text
to
describe
an
issue
,
place
blame
,
identify
victims
,
propose
solutions
, and
ask
readers
to
take
action
on an
issue
.
Texts
such
as these are
framing
documents
. The
research
presented
in this
paper
introduces
the
application
of
statistical
methods
in
text
analytics
as a
means
to
extend
research
involving
the
framing
process
. This
thesis
proposes
that
Latent
Semantic
Analysis
techniques
combined
with
classification
modeling
algorithms
results
in
models
that are
able
to
discover
small
numbers
of
framing
documents
scattered
among
thousands
of
text
documents
. The
models
themselves
provide
insight
into the
character
of
framing
documents
.
Global
warming
was
selected
as the
social
movement
upon
which
to
base
this
study
.
Global
warming
framing
documents
were
collected
from
Internet
sites
, and were
combined
with
other
documents
that
address
global
warming
, but are not
framing
in
nature
. This
corpus
served
to
train
and
test
statistical
models
that not
only
detected
framing
documents
, but
further
classified
these by
framing
task
with
high
accuracy
. These
methods
can
be
implemented
with
commercial
software
and
serve
as a
resource
for the
study
of
both
SMT
and
active
social
movements
.
Subject
Latent semantic indexing
Data mining
Department
Department of Mathematical Sciences
Advisor
Bilisoly, Roger, 1963-
Type
Text
Digital Format
application/pdf
Language
eng
OCLC number
713734985
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