Is the Size of the City Important for the Quality of Urban Life? Comparison of a Small and a Large City
Sustainability,
Год журнала:
2022,
Номер
14(23), С. 15589 - 15589
Опубликована: Ноя. 23, 2022
In
the
recent
past,
question
of
determining
optimal
city
size
in
relation
to
quality
urban
life
(QoUL)
was
raised
inhabitants.
This
article
has
evaluated
correlation
QoUL
index
cities
number
We
also
deal
with
selected
variables
for
which
we
assume
a
relationship
QoUL.
The
authors
who
calculated
indices
equated
its
objective
dimension
considered
as
place.
It
turned
out
that
growth
inhabitants
Slovak
did
not
correlate
improving
life.
Our
examined
two
different
countries
on
scale
0–10
through
questionnaires.
obtained
values
are
subjective
assessment.
From
global
point
view,
one
is
small
and
other
big.
achieved
better
results
international
rankings
life,
it
assumed
this
fact
would
be
reflected
quantification
One
hypothesis
will
achieve
than
large
city.
paper
presents
measurement
correlation.
Язык: Английский
Quality of life issues in rural settlements: Assessment by social media users
Data Science and Management,
Год журнала:
2024,
Номер
7(4), С. 283 - 292
Опубликована: Март 19, 2024
Disparity
in
the
quality
of
life
people
living
rural
and
urban
areas
is
among
major
problems,
often
leading
to
greater
depression
population
compared
those
who
have
access
a
high
standard
living.
The
goal
this
study
was
identify
issues
that
are
fundamental
from
point
view
settlements
typical
for
various
regions
Russian
Federation
with
diverse
geographical,
socioeconomic,
demographic
characteristics.
practical
relevance
our
based
on
identification
scope
problems
related
areas.
value
significance
digital
tracks,
which
can
serve
as
source
information.
data
sources
included
messages
posts
discussing
aspects
published
by
VKontakte.
For
study,
we
used
negative
implications
communities
ten
regions.
These
include
housing
infrastructure
utilities,
transportation,
environment,
telecommunications,
banking,
healthcare,
education.
Язык: Английский
Monitoring Urban Population’s Quality of Life via Digital Footprint: The Case of Novosibirsk
Springer geography,
Год журнала:
2024,
Номер
unknown, С. 21 - 34
Опубликована: Янв. 1, 2024
Язык: Английский
Digital Footprint: Assessing Student Satisfaction with Education Quality
Vysshee Obrazovanie v Rossii = Higher Education in Russia,
Год журнала:
2024,
Номер
33(2), С. 89 - 108
Опубликована: Март 6, 2024
The
COVID-19
pandemic
has
changed
the
way
learning
is
organized
around
world.
Russian
universities
have
also
been
faced
with
need
to
quickly
transfer
all
teaching
an
online
format.
importance
of
student
satisfaction
education
quality
in
increasing,
since
it
important
condition
for
motivation.
paper
shows
that
based
on
analysis
students’
messages
social
network,
possible
observe
and
analyze
overall
dynamics
trends
community
/
efficiency
conduct
a
comparative
identified
characteristic
data
groups
their
totality.
It
shown
reaction
students
particular
university
may
significant
deviations
from
totality
data,
which
reflects
characteristics
events
occurring
at
same
time.
This
indicate
internal
differences
university,
form
appropriate
response
external
events.
To
understand
transition
new
implementation
format
learning.
digital
traces
network
VKontakte
were
analyzed
using
individual
Big
Data
tools
PolyAnalyst
software
platform.
made
trace
changes
mood
and,
example
single
identify
explain
attitude
learning,
as
well
verify
methodology.
methodology
developed
by
authors
makes
detect
problematic
issues
including
moment
occurrence,
relevance,
degree
concern
students.
Such
content
can
be
used
not
only
assess
but
monitor
emergence
any
problems
cause
strong
reactions
part
community,
other
communities
groups.
Язык: Английский
AXIOLOGICAL COMPONENT IN THE STRUCTURE OF VISUAL IMAGES OF THE URBAN ENVIRONMENT
ΠΡΑΞΗMΑ Journal of Visual Semiotics,
Год журнала:
2022,
Номер
1(31), С. 75 - 89
Опубликована: Фев. 10, 2022
Статья
посвящена
возможностям
изучения
ценностного
отношения
к
городской
среде
на
материале
пользовательского
контента
в
социальных
сетях.
Визуальный
образ
города
контексте
цифровых
следов
рассматривается
как
когнитивная
модель
среды,
которой
отражаются
интерпретативные
и
проективные
конструкции
–
субъективные
представления
о
локусах
которые
становятся
освоенными
«местами»,
выражают
определённые
ценностные
ожидания
субъектов
восприятия.
Показано,
что
контент
сетей
реализует
прежде
всего
коммуникативную
функцию
взаимные
между
пользователями,
а
также
пользователей
с
самим
городом.
Утверждается,
межличностная
коммуникация
городом
являются
условием
построения
личностной
идентичности,
так
существования
изменения
самого
города,
который
существует
том
числе
городская
идентичность,
освоенные
места
городского
пространства.
Выявленная
тенденция
апроприации
среды
вполне
отчётливо
выражена
визуальных
материалах
городских
сообществ,
является
новым
значимым
явлением.
Анализ
сетях
показывает,
фотографии
слабо
репрезентируют
витальные
ценности
горожан,
связанные
вопросами
их
бытовой
жизнедеятельности,
однако
них
выражаются
экзистенциальные
потребности
жителей
города.
Доминирующей
ценностно-смысловой
тональностью
оценки
возможность
её
личностного
освоения
присвоения.
The
article
is
dedicated
to
the
possibilities
of
studying
axiological
attitude
towards
urban
environment
on
basis
user-generated
content
in
social
networks.
visual
image
city
context
digital
footprints
considered
be
a
cognitive
model
environment,
which
reflects
interpretative
and
projective
constructions
subjective
ideas
about
loci
that
become
adopted
“places”
express
certain
attitudes
expectations
individuals.
shows
networks
implements,
first
all,
communicative
function
between
users,
them
itself.
Interpersonal
communication
with
are
conditions
for
constructing
personal
identity
existence
change.
exists,
particular,
as
an
identity,
forms
places
space.
described
tendency
appropriation
quite
clearly
expressed
materials
communities,
appear
new
significant
phenomenon.
analysis
photographs
poorly
represent
dwellers’
vital
values
everyday
life,
but
they
their
existential
needs.
dominant
value-semantic
meaning
its
ability
developed
appropriated
by
person
Язык: Русский
Analysis of environmental problems based on social media data (on the example of atmospheric air quality)
E3S Web of Conferences,
Год журнала:
2023,
Номер
458, С. 08010 - 08010
Опубликована: Янв. 1, 2023
The
article
discusses
the
state
and
prospects
of
two
new
methods
to
study
environmental
issues:
Internet
ecology
(iEcology)
conservation
culturomics.
Both
approaches
are
very
similar;
both
them
based
on
big
data
analysis,
which
is
not
directly
meant
solve
issues
(publications
in
social
networks,
search,
photos
videos
posted
platforms,
etc.).
authors
offer
methodology
(as
exemplified
by
quality
atmospheric
air)
from
VK
network
machine
learning
algorithms.
For
content
analysis
we
used
PolyAnalyst
software.
results
publications
air
Magnitogorsk
city
for
2020-2022
presented.
We
identified
433
messages
characterizing
condition
Magnitogorsk.
Our
research
demonstrates
that
ecological
culturomics
can
contribute
situation.
let
us
issue
important
residents
be
as
an
additional
source
information
subjective
assessment
quality.words.
Язык: Английский
Social issues of rural areas: social media open data analysis
E3S Web of Conferences,
Год журнала:
2023,
Номер
462, С. 03008 - 03008
Опубликована: Янв. 1, 2023
This
article
offers
a
new
approach
to
study
social
issues
in
Russian
rural
settlements.
Our
is
based
on
the
analysis
of
digital
footprints
left
by
population
largest
network
VKontakte
(VK).
media
data
and
two
methods
–
big
mining.
For
this
we
used
negative-sounding
messages
posts
published
some
communities
settlements
from
10
(out
85)
regions.
We
PolyAnalyst
software
for
automatic
such
identify
groups
deteriorating
quality
life
those
These
include
housing
utilities
infrastructure,
capital
improvement
transportation
infrastructure;
environmental
issues,
with
availability
poor
telecommunication
banking
healthcare
education
issues;
safety
various
economic
related
homeless
neglected
animals
(dogs);
alcohol
abuse
inefficiency
authorities
Язык: Английский
Validation of machine learning models for automated sentiment determination of Russian-language texts
Vestnik Tomskogo gosudarstvennogo universiteta,
Год журнала:
2022,
Номер
485, С. 206 - 216
Опубликована: Янв. 1, 2022
Sentiment
analysis
is
one
of
the
most
demanded
natural
language
processing
operations
for
solving
applied
problems.
One
key
methods
automated
sentiment
supervised
machine
learning.
In
presence
a
large
selection
ready-made
solutions
determining
tonality,
results
models
give
significant
errors
due
to
complexity
and
contextual
conditionality
linguistic
explication
emotions.
The
article
presents
validation
6
Russian-language
publications
using
research
dataset
–
expertly
marked
300
statements
extracted
from
social
network
messages
on
subject
quality
life
corresponding
types:
positive,
negative,
neutral.
To
evaluate
performance
models,
interannotator
agreement
coefficients
were
used,
in
particular,
Krippendorff’s
alpha,
Cohen’s
kappa
Fleiss’s
coefficients.
obtained
values
showed
low
level
reliability
between
expert
labels
that
assigned
by
models.
Among
experiments
performed,
lowest
achieved
Blanchefort
model
trained
Rusentiment
data,
highest
same
developer
medical
feedback
data.
Based
obtained,
conclusions
drawn
about
common
causes
disagreements
learning
Machine
correctly
identify
tone
texts
if
they
contain
bright
lexical
markers
match
general
statement.
On
contrary,
problems
an
emotionally
charged
message
are
provoked
word
with
opposite
it.
use
emotive
vocabulary
does
not
entire
statement,
marker
words
their
direct
meanings,
uppercase,
forms
complicated
communication
(including
irony,
sarcasm)
remain
risk
factors
attracting
resources:
high
degree
probability
automatic
classification
will
be
able
determine
text.
main
reason
“difficulties”
determination
task
focusing
utterance
as
integral
unit
refusal
focus
individual
formal
indicators.
minimum
communicative
speech.
Capturing
its
semantic
expressive
integrity
super
analysis.
So,
it
still
quite
difficult
trust
such
complex
categorization
It
advisable
associate
prospects
directions
this
area,
first
all,
development
high-quality,
linguistically
sound
training
datasets.
Язык: Английский