Detecting and Analysing Fake Opinions Using Artificial Intelligence Algorithms

نویسندگان

چکیده

In e-commerce and on social media, identifying fake opinions has become a tremendous challenge. Such are widely generated the internet by viewers, also called fraudsters. They write deceptive reviews that purport to reflect actual user experience either promote some products or defame others. target reputations of e-businesses. Their aim is mislead customers make wrong purchase decision selecting undesired products. reviewers often paid rival e-business companies compose positive their and/or negative other companies’ The main objective this paper detect, analyze calculate difference between truthful product reviews. To do this, methodology planned have seven phases: reviewing online products, analyzing features through linguistic enquiry word count (LIWC), preprocessing data clean normalize them, embedding words (Word2Vec) performance using artificial deep-learning algorithms for classifying Two neural network models been evaluated based standard Yelp These bidirectional long-short term memory (BiLSTM) convolutional (CNN). results from comparing two showed BiLSTM model provided higher accuracy detecting than CNN model.

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ژورنال

عنوان ژورنال: Intelligent Automation and Soft Computing

سال: 2022

ISSN: ['2326-005X', '1079-8587']

DOI: https://doi.org/10.32604/iasc.2022.021225