Journal of Psycholinguistic Research,
Journal Year:
2024,
Volume and Issue:
53(2)
Published: March 1, 2024
Abstract
This
paper
examines
the
implications
of
association
patterns
in
our
understanding
mental
lexicon.
By
applying
principles
graph
theory
to
word
data,
we
intend
explore
which
measures
tap
better
into
lexical
knowledge.
To
that
end,
had
different
groups
English
as
Foreign
language
learners
complete
a
fluency
task.
Based
on
these
empirical
study
was
undertaken
corresponding
availability
(LAG).
It
is
observed
aggregation
(mentioned
through
human
coding)
all
tokens
given
topic
allows
emergence
some
lexical-semantic
patterns.
The
most
important
one
existence
key
terms,
featuring
both
high
centrality
sense
network
and
LAG,
define
hub
related
terms.
These
communities
words,
each
organized
around
an
anchor
term,
or
central
word,
are
nicely
apprehended
by
well-known
metric
called
modularity
.
Interestingly
enough,
module
seems
describe
conceptual
class,
showing
collective
lexicon,
at
least
approximated
LA
Graphs,
organised
traversed
semantic
mechanisms
associations
via
hyponymy
hiperonymy,
for
instance.
Another
observation
hubs
can
be
appended,
resulting
diameters
compared
same-sized
random
graphs;
even
so
it
small-world
hypothesis
holds
other
social
natural
networks.
In
this
tutorial
paper,
we
discuss
cognitive
networks
as
powerful
models
for
understanding
human
cognition
and
knowledge.
Cognitive
are
representations
of
associative
knowledge
between
concepts
in
a
system
apt
at
acquiring,
storing,
processing
producing
language,
i.e.
the
mental
lexicon.
network,
nodes
represent
with
links
expressing
relations,
such
semantic,
syntactic,
phonological
visual
connections,
e.g.
“canine”
“dog”
(nodes)
linked
by
“being
synonyms”
(link).
Hence,
mathematical,
measurable
quantifiable
ways.
Can
structure
be
used
to
gain
insights
over
phenomena?
We
explore
research
question
reviewing
recent,
pioneering
key
applications
limitations
across
visual,
auditory,
semantic
language
tasks,
either
healthy
or
clinical
populations.
also
review
modelling
acquisition,
reconstructing
text
content
assessing
creativity
personality
traits
individuals.
Our
gently
introduces
reader
mathematical
notations,
definitions
measures
about
single-layer
multiplex
well
hypergraphs.
Last
but
not
least,
phonological,
syntactic
networks,
guide
through
relevant
psychological
frameworks,
datasets
software
packages
that
might
all
aid
current
future
network
scientists.
Journal of Psycholinguistic Research,
Journal Year:
2024,
Volume and Issue:
53(2)
Published: March 1, 2024
Abstract
This
paper
examines
the
implications
of
association
patterns
in
our
understanding
mental
lexicon.
By
applying
principles
graph
theory
to
word
data,
we
intend
explore
which
measures
tap
better
into
lexical
knowledge.
To
that
end,
had
different
groups
English
as
Foreign
language
learners
complete
a
fluency
task.
Based
on
these
empirical
study
was
undertaken
corresponding
availability
(LAG).
It
is
observed
aggregation
(mentioned
through
human
coding)
all
tokens
given
topic
allows
emergence
some
lexical-semantic
patterns.
The
most
important
one
existence
key
terms,
featuring
both
high
centrality
sense
network
and
LAG,
define
hub
related
terms.
These
communities
words,
each
organized
around
an
anchor
term,
or
central
word,
are
nicely
apprehended
by
well-known
metric
called
modularity
.
Interestingly
enough,
module
seems
describe
conceptual
class,
showing
collective
lexicon,
at
least
approximated
LA
Graphs,
organised
traversed
semantic
mechanisms
associations
via
hyponymy
hiperonymy,
for
instance.
Another
observation
hubs
can
be
appended,
resulting
diameters
compared
same-sized
random
graphs;
even
so
it
small-world
hypothesis
holds
other
social
natural
networks.
