Word statistics in Blogs and RSS feeds: Towards empirical universal evidence

R. Lambiotte, Marcel Ausloos and M. Thelwall

Journal of Informetrics, 2007, vol. 1, issue 4, 277-286

Abstract: We focus on the statistics of word occurrences and of the waiting times between such occurrences in Blogs. Due to the heterogeneity of words’ frequencies, the empirical analysis is performed by studying classes of “frequently-equivalent” words, i.e. by grouping words depending on their frequencies. Two limiting cases are considered: the dilute limit, i.e. for those words that are used less than once a day, and the dense limit for frequent words. In both cases, extreme events occur more frequently than expected from the Poisson hypothesis. These deviations from Poisson statistics reveal non-trivial time correlations between events that are associated with bursts of activities. The distribution of waiting times is shown to behave like a stretched exponential and to have the same shape for different sets of words sharing a common frequency, thereby revealing universal features.

Keywords: Time statistics; Information networks; Zipf law; Activity pattern (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:1:y:2007:i:4:p:277-286

DOI: 10.1016/j.joi.2007.07.001

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