Title: Creating Sentiment Dictionaries via Triangulation
Authors: STEINBERGER JOSEFLENKOVA POLINAEBRAHIM MOHAMEDEHRMANN MAUDVÁZQUEZ SilviaHÜRRIYETOĞLU ALIKABADJOV MIJAILSTEINBERGER RalfTANEV HristoZAVARELLA Vanni
Citation: Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, ACL-HLT 2011 p. 28-36
Publisher: Association of Computational Linguistics ACL
Publication Year: 2011
JRC Publication N°: JRC65731
URI: http://gplsi.dlsi.ua.es/congresos/wassa2011/
http://publications.jrc.ec.europa.eu/repository/handle/JRC65731
Type: Contributions to Conferences
Abstract: The paper presents a semi-automatic approach to creating sentiment dictionaries in many languages. We first produced high-level goldstandard sentiment dictionaries for two languages and then translated them automatically into third languages. Those words that can be found in both target language word lists are likely to be useful because their word senses are likely to be similar to that of the two source languages. These dictionaries can be further corrected, extended and improved. In this paper, we present results that verify our triangulation hypothesis, by evaluating triangulated lists and comparing them to nontriangulated machine-translated word lists.
JRC Institute:Institute for the Protection and Security of the Citizen

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