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Improving the performance of lexicon-based review sentiment analysis method by reducing additional introduced sentiment bias

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  • Hongyu Han
  • Yongshi Zhang
  • Jianpei Zhang
  • Jing Yang
  • Xiaomei Zou

Abstract

Sentiment analysis is widely studied to extract opinions from user generated content (UGC), and various methods have been proposed in recent literature. However, these methods are likely to introduce sentiment bias, and the classification results tend to be positive or negative, especially for the lexicon-based sentiment classification methods. The existence of sentiment bias leads to poor performance of sentiment analysis. To deal with this problem, we propose a novel sentiment bias processing strategy which can be applied to the lexicon-based sentiment analysis method. Weight and threshold parameters learned from a small training set are introduced into the lexicon-based sentiment scoring formula, and then the formula is used to classify the reviews. In this paper, a completed sentiment classification framework is proposed. SentiWordNet (SWN) is used as the experimental sentiment lexicon, and review data of four products collected from Amazon are used as the experimental datasets. Experimental results show that the bias processing strategy reduces polarity bias rate (PBR) and improves performance of the lexicon-based sentiment analysis method.

Suggested Citation

  • Hongyu Han & Yongshi Zhang & Jianpei Zhang & Jing Yang & Xiaomei Zou, 2018. "Improving the performance of lexicon-based review sentiment analysis method by reducing additional introduced sentiment bias," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-11, August.
  • Handle: RePEc:plo:pone00:0202523
    DOI: 10.1371/journal.pone.0202523
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    Cited by:

    1. Wafa Shafqat & Yung-Cheol Byun, 2019. "A Recommendation Mechanism for Under-Emphasized Tourist Spots Using Topic Modeling and Sentiment Analysis," Sustainability, MDPI, vol. 12(1), pages 1-26, December.
    2. Emmanuel Ajayi Olajubu & Ezekiel Aliyu & Adesola Ganiyu Aderounmu & Kamagate Beman Hamidja, 2021. "Managing E-Patient Case Notes in Tertiary Hospitals: A Sub-Saharan African Experience," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 16(4), pages 1-19, October.
    3. Sheema Liza Idris & Masurah Mohamad, 2023. "A Study on Sentiment Analysis on Airline Quality Services: A Conceptual Paper," Information Management and Business Review, AMH International, vol. 15(4), pages 564-576.

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