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An Unification-Based Model for Attitude Prediction

  • Manfred KlennerEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10415)

Abstract

Attitude prediction strives to determine whether an opinion holder is positive or negative towards a given target. We cast this problem as a lexicon engineering task in the context of deep linguistic grammar formalisms such as LFG or HPSG. Moreover, we demonstrate that attitude prediction can be accomplished solely through unification of lexical feature structures. It is thus possible to use our model without altering existing grammars, only the lexicon needs to be adapted. In this paper, we also show how our model can be combined with dependency parsers. This makes our model independent of the availability of deep grammars, only unification as a processing mean is needed.

Keywords

Sentiment Opinion inference Lexical functional grammar 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Computational LinguisticsUniversity of ZurichZürichSwitzerland

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