Identification of Deceptive Reviews by Sentimental Analysis and Characteristics of Reviewers

Xinyu Gao; Shi Li; Yiyin Zhu; Yiting Nan; Zihan Jian; Hongyu Tang
January 2019
Journal of Engineering Science & Technology Review;2019, Vol. 12 Issue 1, p196
Academic Journal
The purchase decisions of customers are influenced by the relevant reviews made by customers. Deceptive reviews are confusing and hard to detect. The existing identification method of deceptive reviews is based on the traditional algorithm of machine learning. However, the methods used to identify deceptive reviews must be improved. In order to improve the accuracy of the identification of deceptive reviews, a novel method integrating sentimental analysis and the characteristics of reviewers was proposed in this study. On the basis of the analysis of the emotional characteristics of the review texts and the behavioural characteristics of the reviewers, a method of deceptive review identification was established. The proposed method analyzed the intensity of emotions, the text similarity, the largest daily publishing comment index, and the extreme rating index on the basis of the feature-weighted model. This model verified the effectiveness of the proposed method. Results show that a direct correlation exists between the unreliability score of users and deceptive review identification. If the score exceeds 0.78, then the reviewer is deemed to be a deceptive reviewer, and the reviews made are deceptive reviews. The proposed method provides a good prospect to identify deceptive reviews.


Related Articles

  • Editorial: Time-Frequency Approach to Radar Detection, Imaging, and Classification. THAYAPARAN, THAYANANTHAN; STANKOVIC, LJUBISA; AMIN, MOENESS; CHEN, VICTOR; COHEN, LEON; BOASHASH, BOUALEM // IET Signal Processing;Aug2010, Vol. 4 Issue 4, p325 

    The article discusses various reports published within the issue, including one on a two-dimensional multiwindow S-method for radar imaging applications, and another on the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm.

  • Guest Editorial. Qiu, Robin G.; He, Matthew // Journal of Networks;Apr2010, Vol. 5 Issue 4, p391 

    The article discusses various reports published within the issue, including one by Hua Jiang and Junhu Ruan on the risk assessment model developed for high-technology projects, one by Jun Tang and Xiaojuan Zhao on the hybrid particle swarm optimization (PSO), and one by Yongquan Zhou and...

  • Recent Trends of Computational Methods in Vibration Problems. Chakraverty, Snehashish; Sahu, Atma; Keong, Choong Kok; Hassan, Saleh M. // Advances in Acoustics & Vibration;2012, Vol. 2012, p1 

    An introduction is presented in which the editor discusses various research papers within the issue on topics including vibration analysis, use of particle swarm optimization and homotopy analysis method.

  • Corrigendum: Collective Motion of Swarming Agents Evolving on a Sphere Manifold: A Fundamental Framework and Characterization. Li, Wei // Scientific Reports;10/30/2015, p15596 

    A correction to the article "Collective Motion of Swarming Agents Evolving on a Sphere Manifold: A Fundamental Framework and Characterization ," by Wei Li, that was published in the October 28,2015 issue is presented.

  • Management Resources Allocation and Scheduling based on Particle Swarm Optimization (PSO). Yangmin BAI // International Journal of Simulation -- Systems, Science & Techno;2016, Vol. 17 Issue 2, p18.1 

    Resources allocation and scheduling can be accomplished in various ways, and there are different criteria for resources allocation and scheduling. In this regard it is generally subject to the values of a particular time and space, but also subject to accounting under certain conditions of time...

  • An Improved Particle Swarm Optimization (IPSO) Approach for Identification and Control of Stable and Unstable Systems. El Gmili, Nada; Mjahed, Mostafa; El Kari, Abdeljalil; Ayad, Hassan // International Review of Automatic Control;May2017, Vol. 10 Issue 3, p229 

    In this paper, an Improved Particle Swarm Optimization (IPSO) technique is generalized to identify and control four systems of different types of behaviors. This was possible thanks to the use of a new initialization strategy of partitioning of particles, which helps PSO to converge faster to...

  • Maximum Power Point Tracking of Photovoltaic Module for Battery Charging Based on Modified Particle Swarm Optimization. Wahjono, Endro; Anggriawan, Dimas Okky; Sunarno, Epyk; Nugraha, Syechu Dwitya; Tjahjono, Anang // International Review on Modelling & Simulations;Feb2017, Vol. 10 Issue 1, p77 

    The Photovoltaic (PV) Module has an important role as a source of renewable energy because it has low maintenance and environmental friendliness. The problem of the PV module is low efficiency. Therefore, this research focus is on the maximization of the PV module. Obtaining the maximum power...

  • Erratum: "An Efficient Particle Swarm Optimization for Large-Scale Hardware/Software Co-Design System". Yan, Xiaohu; He, Fazhi; Hou, Neng; Ai, Haojun // International Journal of Cooperative Information Systems;Dec2017, Vol. 26 Issue 4, p-1 

    No abstract available.

  • Theory of particle swarm optimization: A survey of the power of the swarm's potential. Bassimir, Bernd; Raß, Alexander; Schmitt, Manuel // IT: Information Technology;Aug2019, Vol. 61 Issue 4, p169 

    This paper presents a survey on different showcases for potential measures on particle swarm optimization (PSO). First, a potential is analyzed to prove convergence to non-optimal points. Second, one can apply a minor modification to PSO to prevent convergence to non-optimal points by using an...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics