A Graph-Based Method for Predicting the Helpfulness of Product Opinions
Palavras-chave:Natural Language Processing, Helpfulness Prediction, Opinion Mining.
ResumoThis manuscript presents a new approach to predict the helpfulness of opinions. Usually, researchers in this area use tables of attribute-value to aggregate the features that represent the evaluated texts. In this manuscript, this task is modeled as a network, considering the information of relations among objects in the network (comments, stars, and words). A regularization technique of graphs is used to extract the relevant features of graph structure and, after that, the comments are classified as helpful or unhelpful. We compared our network model with two baselines methods, one based on fuzzy logic and other based on Neural Networks. Our model outperformed the fuzzy logic method in 0.17 of F1 measure and 0.19 of F1 on Neural Network method.
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