Deceptive reviews detection of industrial product
by Song Deng
International Journal of Services Operations and Informatics (IJSOI), Vol. 8, No. 2, 2016

Abstract: Deceptive reviews of products can greatly swing the customer's purchasing decisions. We propose a new method to decrease the influence of deceptive reviews on industrial products by improving the precision of detecting these reviews. The method recognises the deceptive reviews based on the posters' behaviours and the reviews' content. It firstly builds a recognition model of the 'water army' according to the review's quantity, frequency and length, and then builds the content model with five reviews' content features, i.e. the length, the degree of professionalism, the emotional density, the format and the emotional imbalance, and finally detects the deceptive reviews of industrial products by combining an unsupervised clustering algorithm based on F statistics and a feature degree. Our method achieves better results than existing ones according to tests on industrial products of automobiles, mobile phones and computers. Its precision is better than that of identification methods based only on content feature clustering.

Online publication date: Sun, 30-Oct-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Services Operations and Informatics (IJSOI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email