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Will sentiment analysis need subculture? A new data augmentation approach

Author

Listed:
  • Zhenhua Wang
  • Simin He
  • Guang Xu
  • Ming Ren

Abstract

Nowadays, the omnipresence of the Internet has fostered a subculture that congregates around the contemporary milieu. The subculture artfully articulates the intricacies of human feelings by ardently pursuing the allure of novelty, a fact that cannot be disregarded in the sentiment analysis. This paper aims to enrich data through the lens of subculture, to address the insufficient training data faced by sentiment analysis. To this end, a new approach of subculture‐based data augmentation (SCDA) is proposed, which engenders enhanced texts for each training text by leveraging the creation of specific subcultural expression generators. The extensive experiments attest to the effectiveness and potential of SCDA. The results also shed light on the phenomenon that disparate subcultural expressions elicit varying degrees of sentiment stimulation. Moreover, an intriguing conjecture arises, suggesting the linear reversibility of certain subcultural expressions.

Suggested Citation

  • Zhenhua Wang & Simin He & Guang Xu & Ming Ren, 2024. "Will sentiment analysis need subculture? A new data augmentation approach," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(6), pages 655-670, June.
  • Handle: RePEc:bla:jinfst:v:75:y:2024:i:6:p:655-670
    DOI: 10.1002/asi.24872
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    References listed on IDEAS

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