Skip to Main content Skip to Navigation
Conference papers

Review Spam Detection Using Word Embeddings and Deep Neural Networks

Abstract : Review spam (fake review) detection is increasingly important taking into consideration the rapid growth of internet purchases. Therefore, sophisticated spam filters must be designed to tackle the problem. Traditional machine learning algorithms use review content and other features to detect review spam. However, as demonstrated in related studies, the linguistic context of words may be of particular importance for text categorization. In order to enhance the performance of review spam detection, we propose a novel content-based approach that considers both bag-of-words and word context. More precisely, our approach utilizes n-grams and the skip-gram word embedding method to build a vector model. As a result, high-dimensional feature representation is generated. To handle the representation and classify the review spam accurately, a deep feed-forward neural network is used in the second step. To verify our approach, we use two hotel review datasets, including positive and negative reviews. We show that the proposed detection system outperforms other popular algorithms for review spam detection in terms of accuracy and area under ROC. Importantly, the system provides balanced performance on both classes, legitimate and spam, irrespective of review polarity.
Document type :
Conference papers
Complete list of metadata

Cited literature [28 references]  Display  Hide  Download

https://hal.inria.fr/hal-02331287
Contributor : Hal Ifip <>
Submitted on : Thursday, October 24, 2019 - 12:49:31 PM
Last modification on : Thursday, November 19, 2020 - 1:04:16 PM
Long-term archiving on: : Saturday, January 25, 2020 - 2:47:50 PM

File

 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : 2022-01-01

Please log in to resquest access to the document

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Aliaksandr Barushka, Petr Hajek. Review Spam Detection Using Word Embeddings and Deep Neural Networks. 15th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2019, Hersonissos, Greece. pp.340-350, ⟨10.1007/978-3-030-19823-7_28⟩. ⟨hal-02331287⟩

Share

Metrics

Record views

185