UAMCLyR at RepLab 2013: Profiling Task

This paper describes the participation of the Language and Reasoning Group of UAM at RepLab 2013 Profiling evaluation lab. We adopted Distributional Term Representations (DTR) for facing the following problems: i) filtering tweets that are related to an entity, and ii) identifying positive or negative implications for the entity’s reputation, i.e., polarity for reputation. Distributional Term Representations help to overcome, to some extent, the small-length/high-sparsity issues. DTRs are a way to represent terms by means of contextual information, given by term co-occurrence statistics. In order to evaluate our approach, we compared the proposed approach against the traditional Bag-of-Words representation. Obtained results indicate that by means of DTRs it is possible to increase the reliability score of a profiling system.