Paper: UNITOR: Combining Syntactic and Semantic Kernels for Twitter Sentiment Analysis

ACL ID S13-2060
Title UNITOR: Combining Syntactic and Semantic Kernels for Twitter Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

In this paper, the UNITOR system participat- ing in the SemEval-2013 Sentiment Analysis in Twitter task is presented. The polarity de- tection of a tweet is modeled as a classifica- tion task, tackled through a Multiple Kernel approach. It allows to combine the contribu- tion of complex kernel functions, such as the Latent Semantic Kernel and Smoothed Par- tial Tree Kernel, to implicitly integrate syn- tactic and lexical information of annotated ex- amples. In the challenge, UNITOR system achieves good results, even considering that no manual feature engineering is performed and no manually coded resources are em- ployed. These kernels in-fact embed distri- butional models of lexical semantics to deter- mine expressive generalization of tweets.