University of Glasgow Terrier Team / Project Abacá at RepLab 2014: Reputation Dimensions Task

This paper describes our participation in the RepLab 2014 Reputation Dimensions task. The task is a multi-class classification task where tweets relating to an entity of interest are to be classified by their reputation dimension. For our participation we investigate two approaches; Firstly, we use a term’s gini-index score to quantify the term’s representativeness of a specific class and construct class profiles for tweet classification, and secondly, we perform tweet enrichment using a web scale corpus to derive terms representative of a tweet’s class, before training a classifier with the enriched tweets. Our tweet enrichment approach performed exceedingly well, showing that this approach is effective for classifying tweets by their reputation dimensions and a promising direction for