  A salient dynamic property of social media is bursting behavior. In this
paper, we study bursting behavior in terms of the temporal relation between a
preceding baseline fluctuation and the successive burst response using a
frequency time series of 3,000 keywords on Twitter. We found that there is a
fluctuation threshold up to which the burst size increases as the fluctuation
increases and that above the threshold, there appears a variety of burst sizes.
We call this threshold the critical threshold. Investigating this threshold in
relation to endogenous bursts and exogenous bursts based on peak ratio and
burst size reveals that the bursts below this threshold are endogenously caused
and above this threshold, exogenous bursts emerge. Analysis of the 3,000
keywords shows that all the nouns have both endogenous and exogenous origins of
bursts and that each keyword has a critical threshold in the baseline
fluctuation value to distinguish between the two. Having a threshold for an
input value for activating the system implies that Twitter is an excitable
medium. These findings are useful for characterizing how excitable a keyword is
on Twitter and could be used, for example, to predict the response to
particular information on social media.
