Abstract
We describe the system submitted to IBEREVAL-2017 for stance and gender detection in tweets on Catalan Independence [1]. We developed a supervised system using Support Vector Machines with ra- dial basis function kernel to identify the stance and gender of the tweeter using various character level and word level features. Our system achieves a macro-average of F-score(FAVOR) and F-score(AGAINST) of 0.46 for stance detection in both Spanish and Catalan and an accuracy of 64.85% and 44.59% for Gender detection in Spanish and Catalan respectively.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 199-203 |
| Number of pages | 5 |
| Journal | CEUR Workshop Proceedings |
| Volume | 1881 |
| State | Published - Jan 1 2017 |
| Externally published | Yes |
| Event | 2nd Workshop on Evaluation of Human Language Technologies for Iberian Languages, IberEval 2017 - Murcia, Spain Duration: Sep 19 2017 → … |