Ceyda Sanli

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Citation: Sanli C and Lambiotte R (2015) Temporal pattern of online communication spike trains in spreading a scientific rumor: how often, who interacts with whom? Front. Phys. 3:79. We study complex time series (spike trains) of online user communication while spreading messages about the discovery of the Higgs boson in Twitter. We focus on online social(More)
In this paper, we propose a methodology quantifying temporal patterns of nonlinear hashtag time series. Our approach is based on an analogy between neuron spikes and hashtag diffusion. We adopt the local variation, originally developed to analyze local time delays in neuron spike trains. We show that the local variation successfully characterizes nonlinear(More)
We evaluate complex time series of online user communication in Twitter social network. We construct spike trains of each user participating any interaction with any other users in the network. Retweet a message, mention a user in a message, and reply to a message are types of interaction observed in Twitter. By applying the local variation originally(More)
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