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- W1916983229 abstract "How often do individuals perform a given communication activity in the Web, such as posting comments on blogs or news? Could we have a generative model to create communication events with realistic inter-event time distributions (IEDs)? Which properties should we strive to match? Current literature has seemingly contradictory results for IED: some studies claim good fits with power laws; others with non-homogeneous Poisson processes. Given these two approaches, we ask: which is the correct one? Can we reconcile them all? We show here that, surprisingly, both approaches are correct, being corner cases of the proposed Self-Feeding Process (SFP). We show that the SFP (a) exhibits a unifying power, which generates power law tails (including the so-called top-concavity that real data exhibits), as well as short-term Poisson behavior; (b) avoids the i.i.d. fallacy, which none of the prevailing models have studied before; and (c) is extremely parsimonious, requiring usually only one, and in general, at most two parameters. Experiments conducted on eight large, diverse real datasets (e.g., Youtube and blog comments, e-mails, SMSs, etc) reveal that the SFP mimics their properties very well." @default.
- W1916983229 created "2016-06-24" @default.
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- W1916983229 date "2013-05-13" @default.
- W1916983229 modified "2023-09-27" @default.
- W1916983229 title "The self-feeding process" @default.
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- W1916983229 doi "https://doi.org/10.1145/2488388.2488503" @default.
- W1916983229 hasPublicationYear "2013" @default.
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