Aspect Based Sentiment Analysis of Spanish Tweets

on de aspectos Abstract: This article presents the participation of the Intelligent Systems Group (GSI) at Universidad Polit ecnica de Madrid (UPM) in the Sentiment Analysis work- shop focused in Spanish tweets, TASS2015. This year two challenges have been proposed, which we have addressed with the design and development of a modu- lar system that is adaptable to dierent contexts. This system employs Natural Language Processing (NLP) and machine-learning technologies, relying also in pre- viously developed technologies in our research group. In particular, we have used a wide number of features and polarity lexicons for sentiment detection. With regards to aspect detection, we have relied on a graph-based algorithm. Once the challenge has come to an end, the experimental results are promising.

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