Name
Abstract | ||
|---|---|---|
To the best of our knowledge, this is the first work that does drug and adverse event detection from Spanish posts collected from a health social media. First, we created a goldstandard corpus annotated with drugs and adverse events from social media. Then, Textalytics, a multilingual text analysis engine, was applied to identify drugs and possible adverse events. Overall recall and precision were 0.80 and 0.87 for drugs, and 0.56 and 0.85 for adverse events. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3115/v1/W14-1117 | Louhi@EACL |
Field | DocType | Citations |
World Wide Web,Internet privacy,Social media,Precision and recall,Adverse effect,Medicine | Conference | 17 |
PageRank | References | Authors |
0.78 | 16 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Isabel Segura-Bedmar | 1 | 435 | 30.96 |
| ricardo revert | 2 | 22 | 1.16 |
| Paloma Martínez | 3 | 717 | 85.63 |