Search Results for author: Alberto Barrón-Cedeño

Found 19 papers, 3 papers with code

A Checkpoint on Multilingual Misogyny Identification

no code implementations ACL 2022 Arianna Muti, Alberto Barrón-Cedeño

We address the problem of identifying misogyny in tweets in mono and multilingual settings in three languages: English, Italian, and Spanish.

Transfer Learning Zero-Shot Learning

LeaningTower@LT-EDI-ACL2022: When Hope and Hate Collide

no code implementations LTEDI (ACL) 2022 Arianna Muti, Marta Marchiori Manerba, Katerina Korre, Alberto Barrón-Cedeño

Task Hope Speech Detection required models for the automatic identification of hopeful comments for equality, diversity, and inclusion.

Active Learning Hope Speech Detection

Automated Fact-Checking for Assisting Human Fact-Checkers

no code implementations13 Mar 2021 Preslav Nakov, David Corney, Maram Hasanain, Firoj Alam, Tamer Elsayed, Alberto Barrón-Cedeño, Paolo Papotti, Shaden Shaar, Giovanni Da San Martino

The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism.

Fact Checking

Tailoring and Evaluating the Wikipedia for in-Domain Comparable Corpora Extraction

1 code implementation3 May 2020 Cristina España-Bonet, Alberto Barrón-Cedeño, Lluís Màrquez

Our best metric for domainness shows a strong correlation with the human-judged precision, representing a reasonable automatic alternative to assess the quality of domain-specific corpora.

A Context-Aware Approach for Detecting Check-Worthy Claims in Political Debates

no code implementations14 Dec 2019 Pepa Gencheva, Ivan Koychev, Lluís Màrquez, Alberto Barrón-Cedeño, Preslav Nakov

In the context of investigative journalism, we address the problem of automatically identifying which claims in a given document are most worthy and should be prioritized for fact-checking.

Fact Checking

Proppy: A System to Unmask Propaganda in Online News

no code implementations14 Dec 2019 Alberto Barrón-Cedeño, Giovanni Da San Martino, Israa Jaradat, Preslav Nakov

We present proppy, the first publicly available real-world, real-time propaganda detection system for online news, which aims at raising awareness, thus potentially limiting the impact of propaganda and helping fight disinformation.

Propaganda detection

Global Thread-Level Inference for Comment Classification in Community Question Answering

no code implementations EMNLP 2015 Shafiq Joty, Alberto Barrón-Cedeño, Giovanni Da San Martino, Simone Filice, Lluís Màrquez, Alessandro Moschitti, Preslav Nakov

Community question answering, a recent evolution of question answering in the Web context, allows a user to quickly consult the opinion of a number of people on a particular topic, thus taking advantage of the wisdom of the crowd.

Community Question Answering General Classification

Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detection

no code implementations WS 2019 Giovanni Da San Martino, Alberto Barrón-Cedeño, Preslav Nakov

FLC is a fragment-level task that asks for the identification of propagandist text fragments in a news article and also for the prediction of the specific propaganda technique used in each such fragment (18-way classification task).

General Classification Propaganda detection

Automatic Fact-Checking Using Context and Discourse Information

1 code implementation4 Aug 2019 Pepa Atanasova, Preslav Nakov, Lluís Màrquez, Alberto Barrón-Cedeño, Georgi Karadzhov, Tsvetomila Mihaylova, Mitra Mohtarami, James Glass

We study the problem of automatic fact-checking, paying special attention to the impact of contextual and discourse information.

Fact Checking

Studying the History of the Arabic Language: Language Technology and a Large-Scale Historical Corpus

1 code implementation11 Sep 2018 Yonatan Belinkov, Alexander Magidow, Alberto Barrón-Cedeño, Avi Shmidman, Maxim Romanov

Arabic is a widely-spoken language with a long and rich history, but existing corpora and language technology focus mostly on modern Arabic and its varieties.

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