Web-sentiment Analysis Of Public Comments (Public Reviews) For Languages With Limited Resources Such As The Kazakh Language

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Abstract

In the pandemic period, the stay-at-home trend forced businesses to switch their activities to digital mode, for example, app-based payment methods, social distancing via social media platforms, and other digital means have become an integral part of our lives. Sentiment analysis of textual information in user comments is a topical task in emotion AI because user comments or reviews are not homogeneous, they contain sparse context behind, and are misleading both for human and computer. Barriers arise from the emotional language enriched with slang, peculiar spelling, transliteration, use of emoji and their symbolic counterparts, and code-switching.

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APA

Gimadi, D., Evans, R., & Simov, K. (2021). Web-sentiment Analysis Of Public Comments (Public Reviews) For Languages With Limited Resources Such As The Kazakh Language. In International Conference Recent Advances in Natural Language Processing, RANLP (Vol. 2021-September, pp. 65–68). Incoma Ltd. https://doi.org/10.26615/issn.2603-2821.2021_010

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