Training and validation data for the PAN @ SemEval 2019 Task 4: Hyperpartisan News Detection. The data is split into multiple files. The articles are contained in the files with names starting with "articles-" (which validate against the XML schema article.xsd). The ground-truth information is contained in the files with names starting with "ground-truth-" (which validate against the XML schema ground-truth.xsd). The first part of the data (filename contains "bypublisher") is labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com. It contains a total of 750,000 articles, half of which (375,000) are hyperpartisan and half of which are not. Half of the articles that are hyperpartisan (187,...
Overview This dataset contains 10,917 news articles with hierarchical news categories collected bet...
This dataset includes the corpus of online articles on which the paper is based. In detail, the fi...
We have produced a labeled dataset that presents fake news surrounding the conflict in Syria. The da...
Second trial dataset for the SemEval 2019 Task 4: Hyperpartisan News Detection. The dataset contain...
Training, validation, and test data for the PAN @ SemEval 2019 Task 4: Hyperpartisan News Detection....
This paper describes our submission1 to the SemEval 2019 Hyperpartisan News Detection task. Our syst...
Tintin, the system proposed by the CECL for the Hyperpartisan News Detection task of SemEval 2019, i...
We provide a large data set consisting of 2,057 sentences from 90 news articles and annotations of c...
International audienceThis paper describes the Rouletabille participation to the Hyperpartisan News ...
Hyperpartisan news is a kind of news riddled with twisted, untruthful, and often extremely one-sided...
Yellow journalism has increased the spread of hyperpartisan news on the internet. It is very difficu...
News is the main source of information about events in our neighborhood and around the globe. In an ...
We designed a larger and more generic Word Embedding over Linguistic Features for Fake News Detectio...
This is the data used in the paper: Rodrigues, F. and Lourenço, M. and Ribeiro, B. and Pereira, F....
This data set contains material for the purpose of scientific reproducibility of the accompanying ma...
Overview This dataset contains 10,917 news articles with hierarchical news categories collected bet...
This dataset includes the corpus of online articles on which the paper is based. In detail, the fi...
We have produced a labeled dataset that presents fake news surrounding the conflict in Syria. The da...
Second trial dataset for the SemEval 2019 Task 4: Hyperpartisan News Detection. The dataset contain...
Training, validation, and test data for the PAN @ SemEval 2019 Task 4: Hyperpartisan News Detection....
This paper describes our submission1 to the SemEval 2019 Hyperpartisan News Detection task. Our syst...
Tintin, the system proposed by the CECL for the Hyperpartisan News Detection task of SemEval 2019, i...
We provide a large data set consisting of 2,057 sentences from 90 news articles and annotations of c...
International audienceThis paper describes the Rouletabille participation to the Hyperpartisan News ...
Hyperpartisan news is a kind of news riddled with twisted, untruthful, and often extremely one-sided...
Yellow journalism has increased the spread of hyperpartisan news on the internet. It is very difficu...
News is the main source of information about events in our neighborhood and around the globe. In an ...
We designed a larger and more generic Word Embedding over Linguistic Features for Fake News Detectio...
This is the data used in the paper: Rodrigues, F. and Lourenço, M. and Ribeiro, B. and Pereira, F....
This data set contains material for the purpose of scientific reproducibility of the accompanying ma...
Overview This dataset contains 10,917 news articles with hierarchical news categories collected bet...
This dataset includes the corpus of online articles on which the paper is based. In detail, the fi...
We have produced a labeled dataset that presents fake news surrounding the conflict in Syria. The da...