Evaluation of potential Spanish text markers on social posts asfeatures for polarity classification

This work describes the identification and evaluation process of potential text markers for sen-timent analysis. Evaluation of the markers and its use as part of the feature extraction processfrom plain text that is needed for sentiment analysis is presented. Evaluation of text markerobtained as a result of systematic analysis from a corpus over a second one allowed us to iden-tify that emphasized positive words are strong indicators for positive text. The second corpusallowed us to evaluate the relation between the polarity of emphasized words and the text theyappear in. Evaluation of the markers for polarity detection task in combination with a polarizeddictionary produced polarity classification average precision of 56% using only three markers.This are promising results compared to the top 69% obtained using more features and specializeddictionaries for the same taskUniversidad de Costa Rica/[]/UCR/Costa RicaMinisterio de Ciencia, Tecnología y Telecomunicaciones/[]/MICITT/Costa RicaUCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e InformáticaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ingeniería::Centro de Investigaciones en Tecnologías de Información y Comunicación (CITIC)UCR::Vicerrectoría de Docencia::Artes y Letras::Facultad de Letras::Escuela de Filología, Lingüística y Literatur

On the usefulness of lexical and syntactic processing in polarity classification of Twitter messages

NOTICE: This is the authors version of a work that was accepted for publication in Journal o