Sentiment analysis has been extensively investigated during the last years mainly for English language. Currently, existing approaches can be split into two main groups: methods based on the combination of lexical resources and Natural Language Processing (NLP) techniques; and machine learning approaches. This paper introduces the use of lexical databases for Sentiment Analysis of user reviews in Spanish for the accommodation and food and beverage sectors. A global sentiment score has been calculate based on the negative and positive words which appear in the review and using the mentioned lexicon database. The algorithm has been tested with short users online reviews acquired from TripAdvisor.