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Dynamic topic‐related tweet retrieval
Author(s) -
Cotelo Juan M.,
Cruz Fermin L.,
Troyano Jose A.
Publication year - 2014
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.22991
Subject(s) - computer science , publication , information retrieval , set (abstract data type) , context (archaeology) , precision and recall , a priori and a posteriori , task (project management) , graph , social media , world wide web , theoretical computer science , paleontology , philosophy , management , epistemology , advertising , economics , business , biology , programming language
T witter 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 T witter 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 S panish team in the E uro 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 à priori subtopics.