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Title

Dynamical classes of collective attention in Twitter

AuthorsLehmann, Janette; Gonçalves, Bruno; Ramasco, José J. ; Cattuto, Ciro
Issue Date2012
PublisherAssociation for Computing Machinery
CitationWWW 2012 21st World Wide Web Conference 2012: 251-260 (2012)
AbstractMicro-blogging systems such as Twitter expose digital traces of social discourse with an unprecedented degree of resolution of individual behaviors. They offer an opportunity to investigate how a large-scale social system responds to exogenous or endogenous stimuli, and to disentangle the temporal, spatial and topical aspects of users' activity. Here we focus on spikes of collective attention in Twitter, and specifically on peaks in the popularity of hashtags. Users employ hashtags as a form of social annotation, to define a shared context for a specific event, topic, or meme. We analyze a large-scale record of Twitter activity and find that the evolution of hastag popularity over time defines discrete classes of hashtags. We link these dynamical classes to the events the hashtags represent and use text mining techniques to provide a semantic characterization of the hastag classes. Moreover, we track the propagation of hashtags in the Twitter social network and find that epidemic spreading plays a minor role in hastag popularity, which is mostly driven by exogenous factors.
DescriptionComunicación presentada en la 21st international conference on World Wide Web, celebrada en Lyon, del 16 al 20 de abril de 2012.-- Versión Pre-print
URIhttp://hdl.handle.net/10261/79429
DOIhttp://dx.doi.org/10.1145/2187836.2187871
ISBN978-1-4503-1229-5
Appears in Collections:(IFISC) Artículos
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