An Architecture for Opinion Mining on Journalistic Comments: Case of the Senegalese Online Press
| Autor: | Alassane Diédhiou, Khadim Dramé, Marie Ndiaye, Ousmane Sall, Ibrahima Diop, Lamine Faty |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Politics
Exploit Computer science 05 social sciences Sentiment analysis 050602 political science & public administration 0202 electrical engineering electronic engineering information engineering 020206 networking & telecommunications 02 engineering and technology Architecture Collective opinion Data science 0506 political science |
| Zdroj: | Trends and Innovations in Information Systems and Technologies ISBN: 9783030456870 WorldCIST (1) |
| DOI: | 10.1007/978-3-030-45688-7_41 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|