In this paper we present our approach to extract profile information from anonymized tweets for the author profiling task at PAN 2015 [10]. Particularly we explore the versatility of random forest classifiers for the genre and age groups information and random forest regressions to score important aspects of the personality of a user. Furthermore we propose a set of features tailored for this task based on characteristics of the twitters. In particular, our approach relies on previous proposed features for sentiment analysis tasks.

A Random Forest Approach for Authorship Profiling

HERNANDEZ FARIAS, DELIA IRAZU;
2015-01-01

Abstract

In this paper we present our approach to extract profile information from anonymized tweets for the author profiling task at PAN 2015 [10]. Particularly we explore the versatility of random forest classifiers for the genre and age groups information and random forest regressions to score important aspects of the personality of a user. Furthermore we propose a set of features tailored for this task based on characteristics of the twitters. In particular, our approach relies on previous proposed features for sentiment analysis tasks.
2015
CLEF 2015 - Conference and Labs of the Evaluation forum
Toulouse, France
September 8-11
Working Notes of CLEF 2015 - Conference and Labs of the Evaluation forum
CEUR - Workshop Proceedings
1391
1
8
http://ceur-ws.org/Vol-1391/72-CR.pdf
Author Profiling, Random forest, Random Forest Regression, NLP, Machine Learning.
Palomino-Garibay, Alonso; Camacho-González, Adolfo T. ; Fierro-Villaneda, Ricardo A. ; Hernández-Farias, Irazú ; Buscaldi, Davide; Meza Ruiz, Ivan Vla...espandi
File in questo prodotto:
File Dimensione Formato  
72-CR.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 150.97 kB
Formato Adobe PDF
150.97 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1558043
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? ND
social impact