Abstract
Comments from the Senegalese online press can create important opportunities for the socio-economic and political actors of our country. These are potentially promising data and useful sources of information. However, the complexity of these data sets no longer allows current methods of opinion mining to exploit this type of comments. This complexity is caused by ambiguous sentences, out-of-context comments and the use of terms borrowed from national languages. To avoid the risk of not reflecting the collective opinion of Senegalese readers, we are interested in proposing an architecture solely for the purpose of valorizing journalistic comments. The architecture will highlight a new solution to solving these types of problems.
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Faty, L., Ndiaye, M., Dramé, K., Diop, I., Diédhiou, A., Sall, O. (2020). An Architecture for Opinion Mining on Journalistic Comments: Case of the Senegalese Online Press. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1159. Springer, Cham. https://doi.org/10.1007/978-3-030-45688-7_41
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DOI: https://doi.org/10.1007/978-3-030-45688-7_41
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