Add to ORKGWe trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twitter social media data. The system exploits features that we deemed appropriate to profile authors on social media, and that do not characterise too closely the specific usage of Twitter. Our system works on English, Dutch, and Spanish data without any language-specific tuning of features or parameters. Results on the cross-validated training set seem to indicate that features contribute rather equally to the model’s performance
This paper describes approaches for the Author Profiling Shared Task at PAN 2018. The goal was to cl...
User profiling on social media data is normally done within a supervised setting. A typical feature ...
In this report on our participation in the PAN shared task on author profiling, we describe our atte...
We trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twit...
This paper describes various experiments done to investigate author profiling of tweets in 4 differe...
We describe our participation in the PAN 2017 shared task on Author Profiling, identifying authors’ ...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
Automated social media accounts, called bots, gained worldwide considerable importance over the cour...
We provide a training data set that consists of Twitter tweets in English, Spanish and Dutch. The E...
This paper describes an experiment done to investigate author profiling of tweets in English and Spa...
In this paper, we describe one of the approaches of the participation of Universidade de Évora. Our...
Abstract We overview the framework and the results for the Author Profiling Shared Task organised at...
This paper describes approaches for the Author Profiling Shared Task at PAN 2018. The goal was to cl...
User profiling on social media data is normally done within a supervised setting. A typical feature ...
In this report on our participation in the PAN shared task on author profiling, we describe our atte...
We trained an SVM model on tweets to perform user profiling, in terms of gender and age, on non-Twit...
This paper describes various experiments done to investigate author profiling of tweets in 4 differe...
We describe our participation in the PAN 2017 shared task on Author Profiling, identifying authors’ ...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
A simple linear SVM with word and character n-gram features and minimal parameter tuning can identif...
Automated social media accounts, called bots, gained worldwide considerable importance over the cour...
We provide a training data set that consists of Twitter tweets in English, Spanish and Dutch. The E...
This paper describes an experiment done to investigate author profiling of tweets in English and Spa...
In this paper, we describe one of the approaches of the participation of Universidade de Évora. Our...
Abstract We overview the framework and the results for the Author Profiling Shared Task organised at...
This paper describes approaches for the Author Profiling Shared Task at PAN 2018. The goal was to cl...
User profiling on social media data is normally done within a supervised setting. A typical feature ...
In this report on our participation in the PAN shared task on author profiling, we describe our atte...