International audienceThis paper describes the Rouletabille participation to the Hyperpartisan News Detection task. We propose the use of different text classification methods for this task. Preliminary experiments using a similar collection used in (Potthast et al., 2018) show that neural-based classification methods reach state-of-the art results. Our final submission is composed of a unique run that ranks among all runs at 3/49 position for the by-publisher test dataset and 43/96 for the by-article test dataset in terms of Accuracy
Some news headlines mislead readers with overrated or false information, and identifying them in adv...
The classification of news articles is a crucial technology for processing news information, aiding ...
In this paper, the authors report recent results on automatic classification of free text documents ...
International audienceThis paper describes the Rouletabille participation to the Hyperpartisan News ...
This paper describes our submission1 to theSemEval 2019 Hyperpartisan News Detectiontask. Our system...
Tintin, the system proposed by the CECL for the Hyperpartisan News Detection task of SemEval 2019, i...
Yellow journalism has increased the spread of hyperpartisan news on the internet. It is very difficu...
The commercial pressure on media has increasingly dominated the institutional rules of news media, a...
Training and validation data for the PAN @ SemEval 2019 Task 4: Hyperpartisan News Detection. The d...
This paper uses the database as the data source, using bibliometrics and visual analysis methods, to...
The growing availability of data about online information behaviour enables new possibilities for po...
Hyperpartisan news is a kind of news riddled with twisted, untruthful, and often extremely one-sided...
Assigning the submitted text to one of the predetermined categories is required when dealing with ap...
The overabundance of data on social media has posed several challenges to users. First, information ...
The recent advances in information and communication technologies (ICT) have resulted in unprecedent...
Some news headlines mislead readers with overrated or false information, and identifying them in adv...
The classification of news articles is a crucial technology for processing news information, aiding ...
In this paper, the authors report recent results on automatic classification of free text documents ...
International audienceThis paper describes the Rouletabille participation to the Hyperpartisan News ...
This paper describes our submission1 to theSemEval 2019 Hyperpartisan News Detectiontask. Our system...
Tintin, the system proposed by the CECL for the Hyperpartisan News Detection task of SemEval 2019, i...
Yellow journalism has increased the spread of hyperpartisan news on the internet. It is very difficu...
The commercial pressure on media has increasingly dominated the institutional rules of news media, a...
Training and validation data for the PAN @ SemEval 2019 Task 4: Hyperpartisan News Detection. The d...
This paper uses the database as the data source, using bibliometrics and visual analysis methods, to...
The growing availability of data about online information behaviour enables new possibilities for po...
Hyperpartisan news is a kind of news riddled with twisted, untruthful, and often extremely one-sided...
Assigning the submitted text to one of the predetermined categories is required when dealing with ap...
The overabundance of data on social media has posed several challenges to users. First, information ...
The recent advances in information and communication technologies (ICT) have resulted in unprecedent...
Some news headlines mislead readers with overrated or false information, and identifying them in adv...
The classification of news articles is a crucial technology for processing news information, aiding ...
In this paper, the authors report recent results on automatic classification of free text documents ...