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20182020
most citedArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets

36 citations · 45 across the 6 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CL2019★ 1 cited

Tanbih: Get To Know What You Are Reading

Yifan Zhang, Giovanni Da San Martino, Alberto Barrón-Cedeño +10

We introduce Tanbih, a news aggregator with intelligent analysis tools to help readers understanding what's behind a news story. Our system displays news grouped into events and ge…

cs.CL2019★ 36 cited

ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets

Ramy Baly, Alaa Khaddaj, Hazem Hajj +2

Sentiment analysis is a highly subjective and challenging task. Its complexity further increases when applied to the Arabic language, mainly because of the large variety of dialect…

cs.CL2019★ 1 cited

SemEval-2019 Task 8: Fact Checking in Community Question Answering Forums

Tsvetomila Mihaylova, Georgi Karadjov, Pepa Atanasova +3

We present SemEval-2019 Task 8 on Fact Checking in Community Question Answering Forums, which features two subtasks. Subtask A is about deciding whether a question asks for factual…

cs.IR2019

Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection

Abdelrhman Saleh, Ramy Baly, Alberto Barrón-Cedeño +4

In this paper, we describe our submission to SemEval-2019 Task 4 on Hyperpartisan News Detection. Our system relies on a variety of engineered features originally used to detect pr…

cs.IR2019★ 5 cited

Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Media

Ramy Baly, Georgi Karadzhov, Abdelrhman Saleh +2

In the context of fake news, bias, and propaganda, we study two important but relatively under-explored problems: (i) trustworthiness estimation (on a 3-point scale) and (ii) polit…