Identify Fact-checkable Tweets

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

To this end, the FIRE 2018 Information Retrieval from Microblogs during Disasters (IRMiDis) track focused on the identification of factual or fact-checkable tweets and supporting

Preparation of Training Data We randomly choose 100 tweets from the dataset and labeled as a subjective or non-fact-checkable tweet and 83 fact- checkable tweets provided by

We have presented our automatic approach for calculating the factuality score on the basis of number of proper-nouns and quantitative values within a tweet which provided

The task involved classifying tweets posted during a disaster into those which are fact-checkable or factual and which are not, and also match these tweets to relevant news

English. IronITA is a new shared task in the EVALITA 2018 evaluation campaign, focused on the automatic classification of irony in Italian texts from Twitter. It in- cludes two

The aim of the MultiStanceCat task is to detect the authors stances with respect to the Catalan 1st October Referendum (2017) in tweets written in Spanish and Catalan from a

This pattern can be explained by the fact that in the original training dataset we used all tweets for misogyny identification task, but there were fewer data to