Name
Abstract | ||
|---|---|---|
In this paper, we propose a new modeling methodology for Moroccan sociolect recognition used on the social media. It is based on detecting the language of each word in the text: classical Arabic, Tamazight, French or English, determination of the dominant language and processing the words belonging to the Moroccan sociolect. The Interest in this area comes from the huge and simultaneous use of, numbers, Latin script or figures and / or emoticons to speak in Arabic in Morocco which is the result of the country's history. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3090354.3090389 | BDCA |
Field | DocType | ISBN |
Social media,Social network,Classical Arabic,Arabic,Computer science,Sentiment analysis,Latin script,Artificial intelligence,Natural language processing,Sociolect | Conference | 978-1-4503-4852-2 |
Citations | PageRank | References |
1 | 0.43 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fadoua Mansouri | 1 | 1 | 0.77 |
| Sadiq Abdelalim | 2 | 1 | 0.77 |
| Ikram El Azami | 3 | 5 | 2.23 |