Dynamic Topic-Related Tweet Retrieval

Twitter is a social network in which people publish publicly accessible brief, instant messages. With its exponential growth and the public nature and transversality of its contents, more researchers are using Twitter as a source of data for multiple purposes. In this context, the ability to retrieve those messages (tweets) related to a certain topic becomes critical. In this work, we define the topic-related tweet retrieval task and propose a dynamic, graph-based method with which to address it. We have applied our method to capture a data set containing tweets related to the participation of the Spanish team in the Euro 2012 soccer competition, measuring the precision and recall against other simple but commonly used approaches. The results demonstrate the effectiveness of our method, which significantly increases coverage of the chosen topic and is able to capture related but unknown a priori subtopics.