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Emergent user behavior on Twitter modelled by a stochastic differential equation

Data from the social-media site, Twitter, is used to study the fluctuations in tweet rates of brand names. The tweet rates are the result of a strongly correlated user behavior, which leads to bursty collective dynamics with a characteristic 1/f noise. Here we use the aggregated "user interest" in a brand name to model collective human dynamics by a stochastic differential equation with multiplicative noise. The model is supported by a detailed analysis of the tweet rate fluctuations and it reproduces both the exact bursty dynamics found in the data and the 1/f noise.

preprint2015arXivOpen access
Anders MollgaardJoachim Mathiesen
Social and Information Networksphysics.soc-ph
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Open access2 authors2 topics
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
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Anders MollgaardJoachim Mathiesen

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