ELEKTRON HUKUMAT 3.0: FUQAROLAR MUROJAATLARINI QAYTA ISHLASHDA NLP VA SENTIMENT TAHLIL YONDASHUVLARI

Saidrasulov Sherzod Norboy o‘g‘li; Qurbonov Bekzod Nurbek oʻgʻli

Authors

Saidrasulov Sherzod Norboy o‘g‘li Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti
Qurbonov Bekzod Nurbek oʻgʻli Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti

Keywords:

elektron hukumat 3.0, NLP, sentiment tahlil, mashinani o‘qitish, fuqarolar murojaati, davlat xizmatlari, sun’iy intellekt

Abstract

Elektron hukumat dastlab (1.0 bosqichi) davlat xizmatlarini elektron vositalar orqali ko‘rsatishning oddiy usuli sifatida shakllangan bo‘lsa, elektron hukumat 2.0 bosqichida davlat operatsiyalari va xizmatlarini ko‘rsatishda ijtimoiy media va Web 2.0 texnologiyalaridan foydalanish imkoniyati paydo bo‘ldi. Biroq, "elektron hukumat 2.0" atamasi tobora kam ishlatilmoqda, chunki asosiy e’tibor kengroq raqamli transformatsiya tashabbuslariga — xususan, sun’iy intellekt (AI), blokcheyn, virtual va kengaytirilgan reallik texnologiyalariga qaratilmoqda. Shu bois, yangi bosqich — elektron hukumat 3.0 konsepsiyasi shakllandi. U davlat xizmatlarini ko‘rsatish sifatini oshirish, boshqaruvni takomillashtirish, fuqarolar ishtirokini kuchaytirish hamda yangi texnologiyalarni davlat operatsiyalariga integratsiyalash orqali ma’muriy tizimlarning sezgirligi va moslashuvchanligini ta’minlashni ko‘zda tutadi. Ushbu tadqiqotda elektron hukumat 3.0 doirasida fuqarolar murojaatlarini NLP va sentiment tahlil yondashuvlari asosida qayta ishlash zarurati va imkoniyatlari qaraladi.

References

1. Edelman Trust Barometer. (2023). Trust in Government. Edelman.

2. OECD. (2022). Government at a Glance 2021: Trust in Government. OECD Publishing.

3. Pew Research Center. (2023). Public Trust in Government: 1958-2023. Pew Research Center.

4. World Bank. (2022). Digital Government 2020: Tackling the Crisis, Building Back Better. World Bank Group.

5. Accenture. (2021). AI and Sustainability: The Role of Artificial Intelligence in Creating a Sustainable Future. Accenture Research.

6. Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596-615.

7. Misuraca, G., & van Noordt, C. (2020). AI Watch: Artificial Intelligence in public services. European Commission, Joint Research Centre.

8. Mehr, H. (2017). Artificial intelligence for citizen services and government. Harvard Kennedy School, Ash Center for Democratic Governance and Innovation.

9. Berryhill, J., Heang, K. K., Clogher, R., & McBride, K. (2019). Hello, World: Artificial intelligence and its use in the public sector. OECD Working Papers on Public Governance, No. 36, OECD Publishing.

10. Dwivedi, Y. K., Hughes, L., Ismagilova, E., et al. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.

11. Kleinberg, J. M. (1999). Authoritative sources in a hyperlinked environment. Journal of the ACM, 46(5), 604-632.

12. Hreňo, J., Nemčík, M., & Palúch, S. (2011). Semantic interoperability of e-government services. Journal of Systems Integration, 2(3), 23-32.

13. McKinsey Global Institute. (2018). Notes from the AI frontier: Applying AI for social good. McKinsey & Company.

14. Madan, A., & Ashok, M. (2023). AI adoption in government: A sentiment analysis approach. Government Information Quarterly, 40(2), 101789.

15. Ahn, M. J., & Chen, Y. C. (2022). Digital transformation toward AI-enabled public service: The efficient government with digital technologies. Government Information Quarterly, 39(3), 101651.

16. Kumari, R., Jeong, J., Lee, B. H., et al. (2023). Topic modeling and sentiment analysis of global warming Twitter data. Environmental Research, 218, 115003.

17. Lu, J., Mao, E., & Ning, K. (2021). Government artificial intelligence adoption: A systematic literature review. Government Information Quarterly, 38(4), 101596.

18. Eom, S. J., & Lee, J. (2022). Digital government transformation in the COVID-19 pandemic: A systematic review. Government Information Quarterly, 39(2), 101662.

19. Li, W., & Zankova, B. (2021). Public-private partnerships in artificial intelligence: Lessons from smart city implementations. Policy & Internet, 13(4), 541-560.