Publicación: IMPROVING THE AFFECTIVE ANALYSIS IN TEXTS AUTOMATIC METHOD TO DETECT AFFECTIVE INTENSITY IN LEXICONS BASED ON PLUTCHIK'S WHEEL OF EMOTIONS
Fecha
2019
Título de la revista
ISSN de la revista
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Editor
ELECTRONIC LIBRARY
Resumen
THIS PAPER AIMS TO PROPOSE A METHOD FOR AUTOMATICALLY LABELLING AN AFFECTIVE LEXICON WITH INTENSITY VALUES BY USING THE WORDNET SIMILARITY (WS) SOFTWARE PACKAGE WITH THE PURPOSE OF IMPROVING THE RESULTS OF AN AFFECTIVE ANALYSIS PROCESS, WHICH IS RELEVANT TO INTERPRETING THE TEXTUAL INFORMATION THAT IS AVAILABLE IN SOCIAL NETWORKS. THE HYPOTHESIS STATES THAT IT IS POSSIBLE TO IMPROVE AFFECTIVE ANALYSIS BY USING A LEXICON THAT IS ENRICHED WITH THE INTENSITY VALUES OBTAINED FROM SIMILARITY METRICS. ENCOURAGING RESULTS WERE OBTAINED WHEN AN AFFECTIVE ANALYSIS BASED ON A LABELLED LEXICON WAS COMPARED WITH THAT BASED ON ANOTHER LEXICON WITHOUT INTENSITY VALUES.
DESIGN/METHODOLOGY/APPROACH
THE AUTHORS PROPOSE A METHOD FOR THE AUTOMATIC EXTRACTION OF THE AFFECTIVE INTENSITY VALUES OF WORDS USING THE SIMILARITY METRICS IMPLEMENTED IN WS. FIRST, THE INTENSITY VALUES WERE CALCULATED FOR WORDS HAVING AN AFFECTIVE ROOT IN WORDNET. THEN, TO EVALUATE THE EFFECTIVENESS OF THE PROPOSAL, THE RESULTS OF THE AFFECTIVE ANALYSIS BASED ON A LABELLED LEXICON WERE COMPARED TO THE RESULTS OF AN ANALYSIS WITH AND WITHOUT AFFECTIVE INTENSITY VALUES.
