… Here we will characterize the entropy of temporal social networks as a proxy to … nature of
social interaction networks. This entropy will quantify how many typical configuration of social …

… we need to develop a new information theory of complex social networks. … entropy of the
dynamical social network a function of and in the annealed approximation and the large network …

… users perceive the communicated information. The result of … information. The main contribution
of this study is a visualization where the information communicated from a social network …

… The weight is calculated by information entropy. This paper introduces information entropy
to show the closeness of node pairs. We propagate the labels between direct neighbors and …

… not tailored for scale-free networks, like social networks. In order to achieve scalable …
social networks, we propose a partitioning method, EQHyperpart, which utilizes information-Entropy-…

… , an information entropy … entropy of target users, location, time intervals and hashtags are
estimated to quantify the dissemination of events as “how-far about” in real- world using entropy …

… social influence by using information entropy to reveal the relationship between social
interactions and the strength of social … measuring social influence based on information entropy, …

… by entropy. We establish a social relationship graph based on the social network theory that
… on social influence using information entropy to describe the complexity and uncertainty of …

… applied to social network analysis, since entropy describes … social network structure entropy.
In this paper, we use the definition of information entropy to capture temporal social network …

… information carried by the users. The input of the relative entropy formula is precisely the
information … for the similarity calculation of social network information. The measure of node …