TY - JOUR AU - Camargo, Jorge E. AU - Vargas-Calderon, Vladimir AU - Vargas, Nelson AU - Calderón-Benavides, Liliana PY - 2018/09/07 Y2 - 2024/03/29 TI - Sentiment polarity classification of tweets using a extended dictionary JF - Inteligencia Artificial JA - ia VL - 21 IS - 62 SE - Regular Papers DO - 10.4114/intartif.vol21iss62pp1-12 UR - https://journal.iberamia.org/index.php/intartif/article/view/116 SP - 1-12 AB - <p>With the purpose of classifying text based on its sentiment polarity (positive or negative), we proposed an extension of a 68,000 tweets corpus through the inclusion of word definitions from a dictionary of the Real Academia Espa\~{n}ola de la Lengua (RAE). A set of 28,000 combinations of 6 Word2Vec and support vector machine parameters were considered in order to evaluate how positively would affect the inclusion of a RAE's dictionary definitions classification performance. We found that such a corpus extension significantly improve the classification accuracy. Therefore, we conclude that the inclusion of a RAE's dictionary increases the semantic relations learned by Word2Vec allowing a better classification accuracy.</p> ER -