Abstract
Author reputation is a very important variable for evaluating web comments. However, there is no formal definition for calculating its value. This paper presents an adaptation of the approach presented by Sousa et al. (2015) for evaluating the importance of comments about products and services available online, emphasizing measures of author reputation. The implemented adaptation consists in defining six metrics for authors, used as input in a Multilayer Perceptron Artificial Neural Network. On a preliminary evaluation, the Neural Network presented an accuracy of 91.01% on the author classification process. Additionally, an experiment was conduced aiming to compare both approaches, and the results show that the adapted approach had better performance in classifying the importance of comments.
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de Sa, C.A., de S. Santos, R.L., Moura, R.S. (2017). An Approach for Defining the Author Reputation of Comments on Products. In: Frasincar, F., Ittoo, A., Nguyen, L., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2017. Lecture Notes in Computer Science(), vol 10260. Springer, Cham. https://doi.org/10.1007/978-3-319-59569-6_41
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DOI: https://doi.org/10.1007/978-3-319-59569-6_41
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