Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects

no code implementations • WS 2019 • Hala Mulki, Hatem Haddad, Mourad Gridach, Ismail Babao{\u{g}}lu

Arabic sentiment analysis models have employed compositional embedding features to represent the Arabic dialectal content.

Arabic Sentiment Analysis

Tw-StAR at SemEval-2019 Task 5: N-gram embeddings for Hate Speech Detection in Multilingual Tweets

no code implementations • SEMEVAL 2019 • Hala Mulki, Chedi Bechikh Ali, Hatem Haddad, Ismail Babao{\u{g}}lu

In this paper, we describe our contribution in SemEval-2019: subtask A of task 5 {``}Multilingual detection of hate speech against immigrants and women in Twitter (HatEval){''}.

Hate Speech Detection

Tw-StAR at SemEval-2018 Task 1: Preprocessing Impact on Multi-label Emotion Classification

no code implementations • SEMEVAL 2018 • Hala Mulki, Chedi Bechikh Ali, Hatem Haddad, Ismail Babao{\u{g}}lu

A multilabel classification system Tw-StAR was developed to recognize the emotions embedded in Arabic, English and Spanish tweets.

Classification Emotion Classification +4