UNED at RepLab 2012: Monitoring Task.
Tamara Mart, Damiano Spina, Julio A. Gonzalo, Juan del Rosal · CLEF (Online Working Notes/Labs/Workshop) · 2012
This paper describes the UNED participation at RepLab 2012 Monitoring Task. Given an entity and a tweet stream containing the entity's name, the task consists on grouping the tweets in topics and then ranking the identied topics by priority. We tested three dierent systems to deal with the clustering problem: (i) an agglomerative cluster- ing based on term co-occurrences, (ii) a clustering method that considers 'wikied tweets, where each tweet is represented with a set of Wikipedia entries that are semantically related to it and (iii) Twitter-LDA, a topic modeling approach that extends LDA considering some of the intrinsic properties of Twitter data. For the ranking problem, we rely on the in- sight that the priority of a topic depends on the sentiment expressed in the subjective tweets that refer to it. Although none of the proposed systems outperforms the ocial baseline