NETSPAM: AFAKE REVIEW DETECTOR
Today, online reviews play a vital role in the marketing campaign. 90% of consumers read online reviews before buying any product. And 85% of them trust these reviews as much as personal advice. These reviews becomes an essential fact in a business’s success where, genuine reviews can contribute to...
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Veröffentlicht in: | International journal of advanced research in computer science 2018-05, Vol.9 (Special Issue 3), p.313 |
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Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | Today, online reviews play a vital role in the marketing campaign. 90% of consumers read online reviews before buying any product. And 85% of them trust these reviews as much as personal advice. These reviews becomes an essential fact in a business’s success where, genuine reviews can contribute to the welfare of the company and negative reviews can affect the reputation of the company and can lead to economic damage. Since anybody can write a review, it provides an opportunity for spammers to write fake reviews and this maybe done for the sake of money. In this paper, we introduce a novel framework. We are using three different methods to detect fake reviews which is using (i) IP address using meta path (ii)Blocking negative reviews words and using sentiment analysis (iii)Repetition of same words. This experiment’s result outplay the existing approaches. |
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ISSN: | 0976-5697 |
DOI: | 10.26483/ijarcs.v9i0.6257 |