LTRC IIITH at IBEREVAL 2017: Stance and gender detection in tweets on catalan independence

Sahil Swami, Ankush Khandelwal, Manish Shrivastava, Syed Sarfaraz Akhtar

Research output: Contribution to journalConference article

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 languageEnglish (US)
Pages (from-to)199-203
Number of pages5
JournalCEUR Workshop Proceedings
Volume1881
StatePublished - Jan 1 2017
Externally publishedYes
Event2nd Workshop on Evaluation of Human Language Technologies for Iberian Languages, IberEval 2017 - Murcia, Spain
Duration: Sep 19 2017 → …

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