T A D Q I Q O T L A R
jahon ilmiy – metodik jurnali
https://scientific-jl.com
60-son_4-to’plam_Aprel-2025
241
ISSN:3030-3613
NAZARIY ASOSLAR, STATISTIK TAHLIL VA AMALIY TADQIQOTLAR
ASOSIDA INSON XULQ-ATVORINI TAHLIL QILISH
O‘zbekiston Respublikasi
Davlat xavfsizlik xizmati
chegara qo‘shinlari harbiy xizmatchi
Marahimov Oybek Ilhomjon o‘g‘li
Oybekmarahimov@gmail.com
Annotatsiya
Ushbu maqolada inson xulq-atvorining zamonaviy tahlil usullari, ayniqsa sun’iy
intellekt, katta ma’lumotlar va ijtimoiy psixologiya sohalaridagi yangi yondashuvlar
asosida yoritilgan. Tadqiqotlarda insonning kundalik qaror qabul qilish jarayonlari,
ijtimoiy o‘zgarishlarga nisbatan munosabati hamda pandemiya davridagi xulq-atvor
o‘zgarishlari kabi mavzular tahlil qilingan. Hayvonlar xulq-atvori orqali inson
psixologiyasini tushunish va neyron tarmoqlar asosida prognozlash modellariga ham
e’tibor qaratilgan. Ushbu maqola zamonaviy ilmiy natijalarni umumlashtirib, inson
xulq-atvorini chuqurroq anglashga xizmat qiladi.
Annotation
This article explores modern approaches to analyzing human behavior, focusing
on recent developments in artificial intelligence, big data analysis, and social
psychology. The study addresses topics such as everyday decision-making processes,
responses to social changes, and behavioral shifts during the COVID-19 pandemic. It
also highlights the role of animal behavior studies in understanding human psychology
and introduces predictive models based on neural networks. The article synthesizes
contemporary scientific findings to offer a deeper understanding of human behavioral
patterns.
Kirish
Inson xulq-atvori — bu insonlarning o‘zaro munosabatlari, qarorlar qabul qilish
jarayonlari, hissiyotlari va ijtimoiy muhitga munosabati kabi ko‘plab omillarni o‘z
ichiga olgan murakkab tizimdir. So‘nggi yillarda bu sohada olib borilgan tadqiqotlar,
sun'iy intellekt, katta ma'lumotlar tahlili va neyron tarmoqlar kabi ilg‘or
texnologiyalarning qo‘llanilishi orqali yanada chuqurlashgan. Ushbu maqolada inson
xulq-atvorini tahlil qilishda qo‘llanilayotgan nazariy asoslar, statistik tendensiyalar va
amaliy tadqiqotlar yoritiladi.
1. Nazariy asoslar
1.1. Rejalashtirilgan xulq-atvor nazariyasi (TPB)
T A D Q I Q O T L A R
jahon ilmiy – metodik jurnali
https://scientific-jl.com
60-son_4-to’plam_Aprel-2025
242
ISSN:3030-3613
TPB modeliga ko‘ra, insonlarning xatti-harakatlari uchta asosiy komponent
asosida shakllanadi: shaxsiy munosabat (attitude), ijtimoiy norma (subjective norm) va
xatti-harakatga bo‘lgan nazorat hissi (perceived behavioral control). TPB turli ijtimoiy
sohalarda, jumladan texnologiyalarni qabul qilish, sog‘liqni saqlash va ekologik xulq-
atvorni tahlil qilishda qo‘llanilmoqda.
1.2. Sog‘liqni saqlash ishonch modeli (HBM)
HBM insonlar sog‘liqni saqlash bilan bog‘liq xatti-harakatlarga qanday
munosabatda bo‘lishlarini tushuntiradi. Model kasallik xavfi, uni oldini olish
imkoniyati, harakatning foydasi va to‘siqlari kabi elementlarga asoslanadi. COVID-19
pandemiyasi davrida keng qo‘llanilgan.
1.3. Ijtimoiy va kognitiv psixologik yondashuvlar
Ijtimoiy psixologiya shaxslarning jamiyatdagi xatti-harakatlarini, kognitiv
psixologiya esa ularning qaror qabul qilishdagi ichki jarayonlarini tushunishga xizmat
qiladi.
2. Statistik ma’lumotlar
TPB bo‘yicha 2020–2024 yillarda 7400+ ilmiy maqola chop etilgan.
HBM modeli COVID-19 davrida eng ko‘p murojaat qilingan nazariyalardan biri
bo‘ldi.
2022-yilda o‘tkazilgan tadqiqotga ko‘ra, odamlarning 80% dan ortig‘i
pandemiya davrida o‘z xulq-atvorini sog‘liqni saqlash bo‘yicha tavsiyalarga
muvofiq o‘zgartirgan.
3. Amaliy tadqiqotlar
3.1. PEN (Psychology-powered Explainable Neural Network)
Yangi neyron model insonlarning o‘tgan xulq-atvorlari asosida ularning psixologik
holatini prognoz qilish imkonini beradi. Bu model sun’iy intellektni psixologik tahlillar
bilan uyg‘unlashtiradi.
3.2. COVID-19 pandemiyasi tadqiqotlari
Tadqiqotlar ko‘rsatdiki, pandemiya vaqtida odamlarning xulq-atvori sezilarli
darajada o‘zgargan — masalan, sanitariya, izolyatsiya va texnologiyalardan
foydalanish borasida.
3.3. Hayvonlar xulq-atvori asosida insonni tushunish
Qora qushlar ustida o‘tkazilgan tadqiqotlar shuni ko‘rsatadiki, ba’zi hayvonlar
oddiy matematik amallarni tushunish qobiliyatiga ega bo‘lib, bu insonlarning ilk
rivojlanish bosqichlarini tushunishga yordam beradi.
Xulosa
Ushbu maqola zamonaviy ilmiy asoslar va tadqiqotlar orqali inson xulq-
atvorining qanday shakllanishi va qanday tahlil qilinishi mumkinligini ko‘rsatdi.
Nazariy modellar, statistik dalillar va amaliy yondashuvlar orqali bu mavzuning keng
T A D Q I Q O T L A R
jahon ilmiy – metodik jurnali
https://scientific-jl.com
60-son_4-to’plam_Aprel-2025
243
ISSN:3030-3613
va murakkabligi namoyon bo‘ldi. Kelajakdagi tadqiqotlar ushbu yondashuvlarni
yanada chuqurlashtirishi kutilmoqda.
Foydalanilgan adabiyotlar:
1.
Ajzen, I.
(2020).
The theory of planned behavior: Frequently asked questions
.
Organizational
Behavior
and
Human
Decision
Processes
.
https://doi.org/10.1016/j.obhdp.2020.03.004
2.
Liu, Y., et al.
(2024).
Psychology-powered Explainable Neural Network (PEN)
.
Computers
in
Human
Behavior
,
144,
108245.
https://doi.org/10.1016/j.chb.2024.108245
3.
Fischer, I., et al.
(2020).
The behavioural challenge of the COVID-19 pandemic:
IMPACT
.
Royal
Society
Open
Science
,
7(8),
201131.
https://doi.org/10.1098/rsos.201131
4.
Woods, C., et al.
(2022).
Twenty seconds of visual behaviour on social media gives insight
into
personality
.
Scientific
Reports
,
12(1),
1178.
https://doi.org/10.1038/s41598-022-05095-0
5.
Lyu, H., et al.
(2023).
Big data and behavioral dynamics in pandemics
.
Frontiers in Big
Data
,
6,
1099182.
https://doi.org/10.3389/fdata.2023.1099182
6.
Carpenter, C. J.
(2021).
A meta-analysis of the effectiveness of Health Belief Model
variables in predicting behavior
.
Health Communication
, 36(2), 169–179.
https://doi.org/10.1080/10410236.2019.1617446
7.
Betsch, C., et al.
(2020).
COVID-19 risk perception and protective behavior: A
comparison across countries
.
International Journal of Psychology
, 55(S1), 66–76.
https://doi.org/10.1002/ijop.12707
8.
Voelkle, M. C., et al.
(2021).
Dynamic modeling of personality and behavior: A
longitudinal network analysis
.
Journal of Personality and Social Psychology
, 120(3),
635–660.
https://doi.org/10.1037/pspp0000355
9.
Dini, M., et al.
(2023).
Analyzing online behavior to detect psychological traits
.
Artificial
Intelligence
in
Behavioral
Science
,
2(1),
45–59.
https://aibs-journal.org/article/psychological-detection
10.
Niederkrotenthaler, T., et al.
(2021).
Psychological predictors of pandemic behavior: A
meta-review
.
Current
Opinion
in
Psychology
,
42,
45–52.
https://doi.org/10.1016/j.copsyc.2021.06.008
11.
Wang, Y., et al.
(2023).
Artificial intelligence in behavioral prediction: A review of
current
trends
.
Annual
Review
of
Psychology
,
74,
123–144.
https://doi.org/10.1146/annurev-psych-032121-012220
12.
Kuykendall, L., et al.
(2020).
The role of positive psychology in understanding human
behavior
.
Journal
of
Positive
Psychology
,
15(3),
213–229.
https://doi.org/10.1080/17439760.2020.1738539