Producción CyT
Congreso
Autoría
Tomas Alves Salgueiro
;
Emilio Recart
;
Damian Furman
;
Juan Manuel Perez
;
Pablo Nicolás Fernández Larrosa
Fecha
2022
Editorial y Lugar de Edición
JAIIO
Resumen
Información suministrada por el agente en
SIGEVA
Subjective texts have been especially studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this p...
Subjective texts have been especially studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this purpose, we present a polarity dataset of 1,976 headlines mentioning candidates in the 2019 elections at the target level. Preliminary experiments with state-of-the-art classification algorithms based on pre-trained linguistic models suggest that target information is helpful for this task. We make our data and pre-trained models publicly available.
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Palabras Clave
argeted Sentiment AnalysisSpanish datasetpolitical headlinessocial media