Name
Abstract | ||
|---|---|---|
It is difficult to determine the country of origin of the author of a short message based only on the text. This is an even more complex problem when more than one country uses the same native language. In this paper, we address the specific problem of detecting the two main variants of the Portuguese language --- European and Brazilian --- in Twitter micro-blogging data, by proposing and evaluating a set of high-precision features. We follow an automatic classification approach using a Naïve Bayes classifier, achieving 95% accuracy. We find that our system is adequate for real-time tweet classification. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2480362.2480535 | SAC |
Keywords | Field | DocType |
twitter micro-blogging data,native language,microblog message,high-precision feature,main variant,portuguese language,automatic classification approach,bayes classifier,real-time tweet classification,language variant,specific problem,complex problem | Social media,Naive Bayes classifier,Country of origin,Computer science,Portuguese,Microblogging,Natural language processing,Artificial intelligence,Search intent,Machine learning,First language | Conference |
Citations | PageRank | References |
6 | 0.75 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gustavo Laboreiro | 1 | 58 | 4.51 |
| Matko Bošnjak | 2 | 28 | 1.98 |
| Luís Sarmento | 3 | 377 | 31.16 |
| Eduarda Mendes Rodrigues | 4 | 350 | 21.40 |
| Eugénio Oliveira | 5 | 974 | 111.00 |