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This work aims at exploring a triangulation-based methodology for generating a sentiment dictionary in a language from equivalent dictionaries in other languages. Direct machine translation of dictionaries generally leads to incomplete or wrong results, but multilingual translation can help disambiguate and improve these data. More precisely, we want to translate the LIWC dictionary (Linguistic Inquiry and Word Count) into Catalan from the original English dictionary, complemented with other versions in Romance languages close to Catalan, that is, Spanish, French and Italian. Comparing translations from these dictionaries allows us to identify the most reliable solutions, namely, those common to the different languages. Since LIWC classifies words by categories, assigning the correct ones to the chosen translations is also an important issue, specially when the source categories are different. We present …