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Leveraging Readability and Sentiment in Spam Review Filtering Using Transformer Models

  • Published:2023 Issue:2 Volume:45 Page:1439-1454
  • ISSN:0267-6192
  • Container-title:Computer Systems Science and Engineering
  • language:en
  • Short-container-title:

Author:

Kanmani Sujithra,Balasubramanian Surendiran

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

General Computer Science,Theoretical Computer Science,Control and Systems Engineering

Reference47 articles.

1. Trust-aware review spam detection;Xue;2015 IEEE Trustcom/BigDataSE/ISPA,2015

2. Fraud detection in online consumer reviews;Hu;Decision Support Systems,2011

3. Manipulation in digital word-of-mouth: A reality check for book reviews;Hu;Decision Support Systems,2011

4. Readability standards for informed-consent forms as compared with actual readability;Orlow;The New England Journal of Medicine,2003

5. A comparison of classification methods for predicting deception in computer-mediated communication;Zhou;Journal of Management Information Systems,2004

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sentiment analysis using deep learning techniques: a comprehensive review;International Journal of Multimedia Information Retrieval;2023-11-23

2. A Study on the Performance Evaluation of the Convolutional Neural Network–Transformer Hybrid Model for Positional Analysis;Applied Sciences;2023-10-13

3. Efficient Detection of Noise Reviews Over a Large Number of Places;IEEE Access;2023

4. Remote Monitoring and Defect Detection System for Transformer Assembly;2022 International Conference on Knowledge Engineering and Communication Systems (ICKES);2022-12-28
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