Abstract
The present study proposes the implementation of an algorithm to determine the degree of reliability of Business to Consumer Facebook fan pages, to mitigate possible cheating, scams or fraud. We use data mining to filter information from comments expressed by online stores’ customers. The experiment determines a word dictionary to find matches using a Natural Language Processing technique. The main contribution of this research is the analysis of the context of online stores followers and customers that use Facebook as a business tool, this analysis is based on comments as opposed to the classic way of counting the number of likes. This analysis discards wrong and miswritten comments.
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Jácome, D., Tapia, F., Lascano, J.E., Fuertes, W. (2019). Contextual Analysis of Comments in B2C Facebook Fan Pages Based on the Levenshtein Algorithm. In: Rocha, Á., Ferrás, C., Paredes, M. (eds) Information Technology and Systems. ICITS 2019. Advances in Intelligent Systems and Computing, vol 918. Springer, Cham. https://doi.org/10.1007/978-3-030-11890-7_51
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DOI: https://doi.org/10.1007/978-3-030-11890-7_51
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