A Graph-Based Method for Predicting the Helpfulness of Product Opinions

Autores/as

Palabras clave:

Natural Language Processing, Helpfulness Prediction, Opinion Mining.

Resumen

This 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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Biografía del autor/a

Rogério Figueredo de Sousa, Universidade de São Paulo

Doutorando no Instituto de Computação e Matemática Computacional - ICMC da Universidade de São Paulo - São Carlos.

Rafael Tôrres Anchiêta, Universidade de São Paulo

Graduado e Mestre em Ciência da Computação pela Universidade Federal do Piauí. Doutorando em Ciência da Computação pelo Programa de Pós Graduação e Matemática Computacional. ICMC - USP. Tem experiência na área de Ciência da Computação, com ênfase em Processamento de Linguagem Natural e Engenharia de Requisitos.

Maria das Graças Volpe Nunes, Universidade de São Paulo

Possui graduação em Ciências da Computação pela Universidade Federal de São Carlos (1980), mestrado em Ciências da Computação pela Universidade de São Paulo (1985) e doutorado em Informática pela Pontifícia Universidade Católica do Rio de Janeiro (1991). Foi docente e pesquisadora, de 1981 a 2013, no Instituto de Ciências Matemáticas e da Computação, da Universidade de São Paulo (USP) em São Carlos, onde hoje atua como professora senior. Tem experiência na área de Processamento de Língua Natural, atuando principalmente nos seguintes temas: tradução automática, correção ortográfica e gramatical, normalização textual, sumarização automática e análise de sentimentos. 

Citas

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Publicado

2020-07-31

Cómo citar

Sousa, R. F. de, Anchiêta, R. T., & Nunes, M. das G. V. (2020). A Graph-Based Method for Predicting the Helpfulness of Product Opinions. ISys - Brazilian Journal of Information Systems, 13(4), 06–21. Recuperado a partir de https://seer.unirio.br/isys/article/view/9393

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