Estudo sobre Métricas para Definir Reputação do Autor de Comentários em Sites de Vendas de Produtos
Resumo
Conhecer a reputação do autor de textos opinativos é de suma importância para avaliação de comentários na Web. Este artigo apresenta um estudo sobre medidas usadas no processo de avaliação da reputação do autor em sites de vendas de produtos. Realizou-se dois experimentos com as redes neurais Multilayer Perceptron (MLP) e Radial Basis Function (RBF), sendo que a rede MLP obteve melhor desempenho. Comparou-se também a abordagem TOP(X) original, usada para inferir os melhores comentários, com um novo modelo que utiliza rede MLP na dimensão da reputação do autor. Considerando os comentários excelentes e bons, a nova abordagem apresentou resultados significativamente superiores.
Referências
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de Sousa, R. F., Rabelo, R. A. L., and Moura, R. S. (2015). A fuzzy system-based approach to estimate the importance of online customer reviews. In International Conference on Fuzzy Systems (FUZZ-IEEE), pages 1–8.
Gonçalves, P., Dalip, D., Reis, J., Messias, J., Ribeiro, F., Melo, P., Araújo, L., Gonçalves, M., and Benevenuto, F. (2015). Bazinga! caracterizando e detectando sarcasmo e ironia no twitter. In Proc. of the Brazilian Workshop on Social Network Analysis and Mining (BraSNAM).
Halfaker, A., Kittur, A., Kraut, R., and Riedl, J. (2009). A jury of your peers: Quality, experience and ownership in wikipedia. In Proc. of the Int. Symposium on Wikis and Open Collaboration, pages 15:1–15:10. ACM.
Hamilton, R., Vohs, K. D., and McGill, A. L. (2014). We’ll be honest, this won’t be the best article you’ll ever read: The use of dispreferred markers in word-of-mouth communication. Journal of Consumer Research, 41(1):197 – 212.
Hartmann, N., Avanço, L., Balage, P., Duran, M., Nunes, M. D. G. V., Pardo, T., and Aluísio, S. (2014). A large corpus of product reviews in portuguese: Tackling out-of-vocabulary words. In Proc. of the Int. Conference on Language Resources and Evaluation (LREC’14).
Hoisl, B., Aigner, W., and Miksch, S. (2007). Online Communities and Social Computing: Second International Conference, OCSC 2007, pages 362–371. Springer Berlin Heidelberg.
Jackson, P. and Moulinier, I. (2007). Natural language processing for online applications: Text retrieval, extraction and categorization. John Benjamins, Amsterdam.
Kwak, H., Lee, C., Park, H., and Moon, S. (2010). What is twitter, a social network or a news media? In Proc. of the Int. Conference on World Wide Web, pages 591–600. ACM.
Li, M., Huang, L., Tan, C., and Wei, K. (2013). Helpfulness of online product reviews as seen by consumers: Source and content features. Int. J. Electronic Commerce, 17(4):101–136.
Liu, B. (2011). Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer-Verlag New York, Inc., Secaucus, NJ, USA.
Powers, D. M. W. (2011). Evaluation: From precision, recall and f-measure to roc., informedness, markedness & correlation. Journal of Machine Learning Technologies, 2(1):37–63.
Wang, A. H. (2010). Don’t follow me: Spam detection in twitter. In Proc. of the Int. Conference on Security and Cryptography (SECRYPT), pages 1–10.
Weitzel, L., de Oliveira, J. P. M., and Quaresma, P. (2014). Measuring the reputation in user-generated-content systems based on health information. Procedia Computer Science, 29:364 – 378.
Weng, J., Lim, E.-P., Jiang, J., and He, Q. (2010). Twitterrank: Finding topic-sensitive influential twitterers. In Proc. of the Int. Conference on Web Search and Data Mining, pages 261–270. ACM.
Wöhner, T., Köhler, S., and Peters, R. (2011). Automatic reputation assessment in wikipedia. In Proc. of the Int. Conference on Information Systems.
Zhao, H., Ye, S., Bhattacharyya, P., Rowe, J., Gribble, K., and Wu, S. F. (2010). Socialwiki: Bring order to wiki systems with social context. In Social Informatics - Second International Conference, SocInfo, pages 232–247.
Adler, B. T., de Alfaro, L., and Pye, I. (2010). Detecting wikipedia vandalism using wikitrust.
Aggarwal, A. and Kumaraguru, P. (2014). Followers or phantoms? an anatomy of purchased twitter followers. CoRR.
Cappelletti, R. and Sastry, N. (2012). IARank: Ranking users on twitter in near real-time, based on their information amplification potential. In SocialInformatics, pages 70–77.
Carvalho, P., Sarmento, L., Silva, M. J., and de Oliveira, E. (2009). Clues for detecting irony in user-generated contents: Oh...!! it’s ”so easy”;-). In Proc. of the Int. Workshop on Topic-sentiment Analysis for Mass Opinion, pages 53–56.
de Sousa, R. F., Rabelo, R. A. L., and Moura, R. S. (2015). A fuzzy system-based approach to estimate the importance of online customer reviews. In International Conference on Fuzzy Systems (FUZZ-IEEE), pages 1–8.
Gonçalves, P., Dalip, D., Reis, J., Messias, J., Ribeiro, F., Melo, P., Araújo, L., Gonçalves, M., and Benevenuto, F. (2015). Bazinga! caracterizando e detectando sarcasmo e ironia no twitter. In Proc. of the Brazilian Workshop on Social Network Analysis and Mining (BraSNAM).
Halfaker, A., Kittur, A., Kraut, R., and Riedl, J. (2009). A jury of your peers: Quality, experience and ownership in wikipedia. In Proc. of the Int. Symposium on Wikis and Open Collaboration, pages 15:1–15:10. ACM.
Hamilton, R., Vohs, K. D., and McGill, A. L. (2014). We’ll be honest, this won’t be the best article you’ll ever read: The use of dispreferred markers in word-of-mouth communication. Journal of Consumer Research, 41(1):197 – 212.
Hartmann, N., Avanço, L., Balage, P., Duran, M., Nunes, M. D. G. V., Pardo, T., and Aluísio, S. (2014). A large corpus of product reviews in portuguese: Tackling out-of-vocabulary words. In Proc. of the Int. Conference on Language Resources and Evaluation (LREC’14).
Hoisl, B., Aigner, W., and Miksch, S. (2007). Online Communities and Social Computing: Second International Conference, OCSC 2007, pages 362–371. Springer Berlin Heidelberg.
Jackson, P. and Moulinier, I. (2007). Natural language processing for online applications: Text retrieval, extraction and categorization. John Benjamins, Amsterdam.
Kwak, H., Lee, C., Park, H., and Moon, S. (2010). What is twitter, a social network or a news media? In Proc. of the Int. Conference on World Wide Web, pages 591–600. ACM.
Li, M., Huang, L., Tan, C., and Wei, K. (2013). Helpfulness of online product reviews as seen by consumers: Source and content features. Int. J. Electronic Commerce, 17(4):101–136.
Liu, B. (2011). Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer-Verlag New York, Inc., Secaucus, NJ, USA.
Powers, D. M. W. (2011). Evaluation: From precision, recall and f-measure to roc., informedness, markedness & correlation. Journal of Machine Learning Technologies, 2(1):37–63.
Wang, A. H. (2010). Don’t follow me: Spam detection in twitter. In Proc. of the Int. Conference on Security and Cryptography (SECRYPT), pages 1–10.
Weitzel, L., de Oliveira, J. P. M., and Quaresma, P. (2014). Measuring the reputation in user-generated-content systems based on health information. Procedia Computer Science, 29:364 – 378.
Weng, J., Lim, E.-P., Jiang, J., and He, Q. (2010). Twitterrank: Finding topic-sensitive influential twitterers. In Proc. of the Int. Conference on Web Search and Data Mining, pages 261–270. ACM.
Wöhner, T., Köhler, S., and Peters, R. (2011). Automatic reputation assessment in wikipedia. In Proc. of the Int. Conference on Information Systems.
Zhao, H., Ye, S., Bhattacharyya, P., Rowe, J., Gribble, K., and Wu, S. F. (2010). Socialwiki: Bring order to wiki systems with social context. In Social Informatics - Second International Conference, SocInfo, pages 232–247.
Publicado
26/07/2018
Como Citar
DE SÁ, Carlos Augusto; MOURA, Raimundo Santos.
Estudo sobre Métricas para Definir Reputação do Autor de Comentários em Sites de Vendas de Produtos. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 7. , 2018, Natal.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 109-120.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2018.3584.
