Identifying the features of reputable users in eWOM communities by using Particle Swarm Optimization

Electronic Word-of-Mouth communities have become popular over the last several years as websites where people can share their online reviews about any type of product or service. As a mechanism to improve trust, posted reviews can also be scored by the rest of the community in terms of helpfulness,...

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Bibliographic Details
Published in:Technological forecasting & social change 2018-08, Vol.133, p.220-228
Main Authors: Martínez-Torres, M.R., Arenas-Marquez, F.J., Olmedilla, M., Toral, S.L.
Format: Article
Language:English
Subjects:
Classification
Classification rules
Communities
Credibility
Electronic Word-of-Mouth communities
Evolutionary algorithms
Optimization algorithms
Particle Swarm Optimization
Reputable users
Reputations
Studies
Trust
Websites
Word of mouth advertising
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Summary:Electronic Word-of-Mouth communities have become popular over the last several years as websites where people can share their online reviews about any type of product or service. As a mechanism to improve trust, posted reviews can also be scored by the rest of the community in terms of helpfulness, so users can reach a high level of reputation through their interactions with other users and can thus increase their credibility. The aim of this paper is to investigate the main patterns of activity that characterize reputable users by using a set of classification rules. However, the class of reputable users is only a fraction of the total number of users. Due to the imbalance between the classes, i.e., reputable and non-reputable users, and the high dimensionality of the problem, an evolutionary computation algorithm such as Particle Swarm Optimization (PSO) is applied to obtain the main activity patterns of reputable users. Obtained results can help us better understand the mechanism of trust in eWOM communities and avoid the undesirable manipulation of reputations by false accounts. •Identification of the main patterns of activity that characterize reputable users•Application of Swarm Intelligence to solve classification of imbalanced classes•Reputed users can be characterized by their rating values and trusted-by network•Both the level-1 and 2 neighbourhood of the trusted-by network should be considered
ISSN:0040-1625
1873-5509
DOI:10.1016/j.techfore.2018.04.017