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March 1, 2026International Journal of Complexity in Applied Science and Technology0 citationsOpen Access

A Comparative Study of NLP Systems for Sentiment Polarity Classification across Different Domains and Genres

VSVincenzo Sammartino

Key Points

  • The central aim is to assess how different NLP systems perform in sentiment polarity classification across varied domains and genres.
  • Comparative analysis of multiple NLP systems
  • Evaluation of sentiment polarity across different text genres
  • Use of performance metrics to measure effectiveness
  • Variation in classification accuracy across different domains
  • Identified strengths and weaknesses of specific NLP systems
  • Recommendations for best practices in sentiment analysis based on genre

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Vincenzo Sammartino (2026) studied this question.

synapsesocial.com/papers/69a3d887ec16d51705d2f6c4https://doi.org/10.1504/ijcast.2026.10076620
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