research product . 2015

An experimental study for the Cross Domain Author Profiling classification

Garciarena Ucelay, María José; Villegas, María Paula; Cagnina, Leticia; Errecalde, Marcelo Luis;
Open Access English
  • Published: 01 Jan 2015
  • Country: Argentina
Abstract
Author Profiling is the task of predicting characteristics of the author of a text, such as age, gender, personality, native language, etc. This is a task of growing importance due to the potential applications in security, crime detection and marketing, among others. An interesting point is to study the robustness of a classifier when it is trained with a dataset and tested with others containing different characteristics. Commonly this is called cross domain experimentation. Although different cross domain studies have been done for datasets in English language, for Spanish it has recently begun. In this context, this work presents a study of cross domain classification for the author profiling task in Spanish. The experimental results showed that using corpora with different levels of formality we can obtain robust classifiers for the author profiling task in Spanish language.
Red de Universidades con Carreras en Informática (RedUNCI)
XII Workshop Bases de Datos y Minería de Datos (WBDDM)
Subjects
free text keywords: Ciencias Informáticas, Natural Language Processing, cross domain classification, author profiling
Communities
  • Digital Humanities and Cultural Heritage
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