Abstract
One of the major problem for recommendation services is commercial astroturfing. This work is devoted to constructing a model capable of detecting astroturfing in customer reviews based on network analysis. The model uses projecting a multipartite network to a unipartite graph, for which we detect communities and represent actors with falsified opinions.
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Acknowledgements
The article was supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5-100’ and RFBR grant 16-29-09583 “Methodology, techniques and tools of recognition and counteraction to organized information campaigns on the Internet”.
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Kostyakova, N., Karpov, I., Makarov, I., Zhukov, L.E. (2018). Commercial Astroturfing Detection in Social Networks. In: Kalyagin, V., Pardalos, P., Prokopyev, O., Utkina, I. (eds) Computational Aspects and Applications in Large-Scale Networks. NET 2016. Springer Proceedings in Mathematics & Statistics, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-96247-4_23
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DOI: https://doi.org/10.1007/978-3-319-96247-4_23
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