67 research outputs found
From coincidence to purposeful flow? properties of transcendental information cascades
In this paper, we investigate a method for constructing cascades of information co-occurrence, which is suitable to trace emergent structures in information in scenarios where rich contextual features are unavailable. Our method relies only on the temporal order of content-sharing activities, and intrinsic properties of the shared content itself. We apply this method to analyse information dissemination patterns across the active online citizen science project Planet Hunters, a part of the Zooniverse platform. Our results lend insight into both structural and informational properties of different types of identifiers that can be used and combined to construct cascades. In particular, significant differences are found in the structural properties of information cascades when hashtags as used as cascade identifiers, compared with other content features. We also explain apparent local information losses in cascades in terms of information obsolescence and cascade divergence; e.g., when a cascade branches into multiple, divergent cascades with combined capacity equal to the original
Why Do Cascade Sizes Follow a Power-Law?
We introduce random directed acyclic graph and use it to model the
information diffusion network. Subsequently, we analyze the cascade generation
model (CGM) introduced by Leskovec et al. [19]. Until now only empirical
studies of this model were done. In this paper, we present the first
theoretical proof that the sizes of cascades generated by the CGM follow the
power-law distribution, which is consistent with multiple empirical analysis of
the large social networks. We compared the assumptions of our model with the
Twitter social network and tested the goodness of approximation.Comment: 8 pages, 7 figures, accepted to WWW 201
Why does attention to web articles fall with time?
We analyze access statistics of a hundred and fifty blog entries and news
articles, for periods of up to three years. Access rate falls as an inverse
power of time passed since publication. The power law holds for periods of up
to thousand days. The exponents are different for different blogs and are
distributed between 0.6 and 3.2. We argue that the decay of attention to a web
article is caused by the link to it first dropping down the list of links on
the website's front page, and then disappearing from the front page and its
subsequent movement further into background. The other proposed explanations
that use a decaying with time novelty factor, or some intricate theory of human
dynamics cannot explain all of the experimental observations.Comment: To appear in JASIS
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