ASPEKTGA ASOSLANGAN SENTIMENT TAHLILIDA ASPEKTLARNI ANIQLASH VA ULARNING TURLARI
Keywords:
aspektga asoslangan sentiment tahlil, ABSA, aspekt, sentiment, implicit, explicit, o‘zbek tili, aspektni aniqlashAbstract
Mazkur maqolada aspektga asoslangan sentiment tahlil (Aspect-Based Sentiment Analysis – ABSA) yondashuvi doirasida aspekt tushunchasi, uning turlari va amaliy ahamiyati o‘rganiladi. Tadqiqotda sentiment tahlilining an’anaviy usullari bilan solishtirganda ABSA yondashuvining afzalliklari asoslab berilgan hamda matndagi fikrlarni chuqur va aniq tahlil qilishdagi o‘rni yoritilgan. Aspektlar ifodalanishiga ko‘ra aniq va yashirin, tuzilishiga ko‘ra esa oddiy va murakkab turlarga ajratilib, ularning lingvistik va semantik xususiyatlari batafsil tahlil qilinadi. Shuningdek, aspektlarning turli sohalarda – elektron tijorat, xizmat ko‘rsatish, texnologiya, ta’lim va ijtimoiy tarmoqlarda qo‘llanilishi ko‘rib chiqilib, har bir domen uchun xos bo‘lgan aspektlar tizimlashtiriladi. Tadqiqotda aspektlarni aniqlash jarayonining amaliy ahamiyati alohida yoritilib, uning qaror qabul qilish, marketing tahlili, tavsiya tizimlari va jamoatchilik fikrini monitoring qilishdagi roli asoslab beriladi. O‘zbek tilida aspektga asoslangan sentiment tahlilning rivojlanish darajasi ham tahlil qilinib, mavjud muammolar, jumladan, lingvistik resurslarning yetishmasligi, morfologik murakkablik va kontekstga bog‘liqlik kabi omillar ko‘rsatib o‘tiladi. Tadqiqot natijalari o‘zbek tilida ABSA tizimlarini rivojlantirish uchun nazariy va amaliy asos bo‘lib xizmat qiladi.
Downloads
References
Pontiki, M., et al. (2014). SemEval-2014 Task 4: Aspect Based Sentiment Analysis. COLING. pp. 27–35.
Pontiki, M., et al. (2016). SemEval-2016 Task 5: Aspect Based Sentiment Analysis. ACL. pp. 19–30.
Zhang, L., Wang, S., Liu, B. (2018). Deep learning for sentiment analysis: A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(4).
Feng, S., Wang, B., Yang, Z., & Ouyang, J. (2022). Aspect-based sentiment analysis with attention-assisted graph and variational sentence representation. Knowledge-based systems, 258, 109975.
Jazuli, A., Widowati, & Kusumaningrum, R. (2024). Optimizing aspect-based sentiment analysis using BERT for comprehensive analysis of Indonesian student feedback. Applied Sciences, 15(1), 172.
Hua, Y. C., Denny, P., Wicker, J., & Taskova, K. (2024). A systematic review of aspect-based sentiment analysis: domains, methods, and trends. Artificial Intelligence Review, 57(11), 296.
Kontonatsios, G., Clive, J., Harrison, G., Metcalfe, T., Sliwiak, P., Tahir, H., & Ghose, A. (2023). FABSA: An aspect-based sentiment analysis dataset of user reviews. Neurocomputing, 562, 126867.
Kuriyozov, E., Matlatipov, S., Alonso, M. A., Gómez-Rodríguez, C. (2019). Construction and evaluation of sentiment datasets for low-resource languages: The case of Uzbek.
In: Language and Technology Conference (LTC 2019), Springer, Cham, pp. 232–243.
Matlatipov, S., Rahimboeva, H., Rajabov, J., & Kuriyozov, E. (2022). Uzbek sentiment analysis based on local restaurant reviews. arXiv preprint arXiv:2205.15930.
Mengliev, D. B., Akhmedov, E. Y., Barakhnin, V. B., Hakimov, Z. A., & Alloyorov, O. M. (2023, November). Utilizing lexicographic resources for sentiment classification in Uzbek language. In 2023 IEEE XVI International Scientific and Technical Conference Actual Problems of Electronic Instrument Engineering (APEIE) (pp. 1720-1724). IEEE.
Elov, B., & Xusainova, Z. (2025). SENTIMENT TAHLILIDA SO ‘Z TURKUMLARINING ROLI. COMPUTER LINGUISTICS: PROBLEMS, SOLUTIONS, PROSPECTS, 1(1).
Downloads
Published
Conference Proceedings Volume
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
