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New Technology of Library and Information Service  2014, Vol. 30 Issue (9): 81-90    DOI: 10.11925/infotech.1003-3513.2014.09.11
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Research on Product Review Attribute-Based of Emotion Evaluate Review Spam Detection
Chen Yanfang1,2, Li Zhiyu1,2,3
1. School of Information Management, Central China Normal University, Wuhan 430079, China;
2. E-Commerce Research Center of Hubei Province, Central China Normal University, Wuhan 430079, China;
3. School of Information, Renmin University of China, Beijing 100872, China
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Abstract  

[Objective] A model of Review Attribute of Product-Based Emotion Evaluate(RAPBEE) Model is proposed to detect fake reviews of online products. [Methods] Combined with the known research on the reviews effectiveness evaluation, the measuring method of review attribute of product-based emotion outlier detection is used to comprehensive sort the reliability of the reviews, so as to detect the fake reviews. [Results] The test data set is based on the R language to run the model, the results show that after calculated by the RAPBEE model the review sequencing has achieved 86.2% of agreement compared with the real situation which indicates that the RAPBEE model has a strong practical ability and fitness. [Limitations] The model stability depends on the modeling way of the attribute dictionary and the method also can be improved when dealing with large amounts of data set(Big Data). [Conclusions] The paper proposes a new method to deal with the Chinese fake reviews detection of online products, and this method has a strong expandability in reality.

Key wordsEmotion tendency      Fake reviews      Spam reviews      Reviews of online products      Reviews spam detection     
Received: 24 March 2014      Published: 20 October 2014
:  TP391  

Cite this article:

Chen Yanfang, Li Zhiyu. Research on Product Review Attribute-Based of Emotion Evaluate Review Spam Detection. New Technology of Library and Information Service, 2014, 30(9): 81-90.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.09.11     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I9/81

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