1 code implementation • EMNLP 2020 • Ramy Baly, Giovanni Da San Martino, James Glass, Preslav Nakov
We explore the task of predicting the leading political ideology or bias of news articles.
1 code implementation • ACL 2020 • Ramy Baly, Georgi Karadzhov, Jisun An, Haewoon Kwak, Yoan Dinkov, Ahmed Ali, James Glass, Preslav Nakov
Alternatively, we can profile entire news outlets and look for those that are likely to publish fake or biased content.
no code implementations • IJCNLP 2019 • Yifan Zhang, Giovanni Da San Martino, Alberto Barrón-Cedeño, Salvatore Romeo, Jisun An, Haewoon Kwak, Todor Staykovski, Israa Jaradat, Georgi Karadzhov, Ramy Baly, Kareem Darwish, James Glass, Preslav Nakov
We introduce Tanbih, a news aggregator with intelligent analysis tools to help readers understanding what's behind a news story.
no code implementations • SEMEVAL 2019 • Tsvetomila Mihaylova, Georgi Karadjov, Pepa Atanasova, Ramy Baly, Mitra Mohtarami, Preslav Nakov
For subtask A, all systems improved over the majority class baseline.
2 code implementations • 25 May 2019 • Ramy Baly, Alaa Khaddaj, Hazem Hajj, Wassim El-Hajj, Khaled Bashir Shaban
Sentiment analysis is a highly subjective and challenging task.
no code implementations • SEMEVAL 2019 • Abdelrhman Saleh, Ramy Baly, Alberto Barrón-Cedeño, Giovanni Da San Martino, Mitra Mohtarami, Preslav Nakov, James Glass
In this paper, we describe our submission to SemEval-2019 Task 4 on Hyperpartisan News Detection.
no code implementations • NAACL 2019 • Ramy Baly, Georgi Karadzhov, Abdelrhman Saleh, James Glass, Preslav Nakov
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) political ideology detection (left/right bias on a 7-point scale) of entire news outlets, as opposed to evaluating individual articles.
2 code implementations • EMNLP 2018 • Ramy Baly, Georgi Karadzhov, Dimitar Alexandrov, James Glass, Preslav Nakov
We present a study on predicting the factuality of reporting and bias of news media.
no code implementations • NAACL 2018 • Ramy Baly, Mitra Mohtarami, James Glass, Lluis Marquez, Alessandro Moschitti, Preslav Nakov
A reasonable approach for fact checking a claim involves retrieving potentially relevant documents from different sources (e. g., news websites, social media, etc.
no code implementations • NAACL 2018 • Mitra Mohtarami, Ramy Baly, James Glass, Preslav Nakov, Lluis Marquez, Alessandro Moschitti
We present a novel end-to-end memory network for stance detection, which jointly (i) predicts whether a document agrees, disagrees, discusses or is unrelated with respect to a given target claim, and also (ii) extracts snippets of evidence for that prediction.
Ranked #6 on Fake News Detection on FNC-1
no code implementations • SEMEVAL 2017 • Ramy Baly, Gilbert Badaro, Ali Hamdi, Rawan Moukalled, Rita Aoun, Georges El-Khoury, Ahmad Al Sallab, Hazem Hajj, Nizar Habash, Khaled Shaban, Wassim El-Hajj
While sentiment analysis in English has achieved significant progress, it remains a challenging task in Arabic given the rich morphology of the language.
no code implementations • WS 2017 • Ramy Baly, Gilbert Badaro, Georges El-Khoury, Rawan Moukalled, Rita Aoun, Hazem Hajj, Wassim El-Hajj, Nizar Habash, Khaled Shaban
Opinion mining in Arabic is a challenging task given the rich morphology of the language.
no code implementations • COLING 2016 • Francisco Guzm{\'a}n, Houda Bouamor, Ramy Baly, Nizar Habash
Evaluation of machine translation (MT) into morphologically rich languages (MRL) has not been well studied despite posing many challenges.