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- W2616152685 abstract "Electronic Word-of-Mouth (eWOM) communities has popularized during the last years as communities where people share their online reviews about any type of product or services. Though the interactions with other users, people reach a reputation within the community that make their reviews more trustable. The aim of this paper is to investigate the main patterns of activity that characterizes reputed users. Due to the size of eWOM communities, an evolutionary computation algorithm such as Particle Swarm Optimizacion (PSO) will be used to obtain their main activity features. Obtained results can help to better understand the mechanism of trust in eWOM communities and also to avoid the manipulation of reputation." @default.
- W2616152685 created "2017-05-26" @default.
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- W2616152685 date "2016-08-01" @default.
- W2616152685 modified "2023-10-01" @default.
- W2616152685 title "Features of Reputed Users in eWOM Using Evolutionary Computation" @default.
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- W2616152685 doi "https://doi.org/10.1109/dese.2016.36" @default.
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