Complexity, Heterogeneity, and the Methods of Statistical Physics in Economics by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9789811548062
Publisher: Springer Singapore

8.4.5.1 Applications

The type of feedback dynamics discussed above is widely used to characterize the importance of nodes in a network. Already Google’s early version of the PageRank algorithm built on this. A related measure, DebtRank was introduced to quantify the importance of institutions in a financial network (Battiston et al. 2012). Further, the approach has found an important application to model online social networks (OSN) (Schweitzer et al. 2020). For example in Twitter or Instagram, the reputation of users is not just determined by the number of followers, but also by their reputation. It makes all the difference, whether individual i is a follower of the famous actor z, or the other way round.

Social networks are often characterized by a core-periphery structure, where the core contains a subset of well-connected users. This is important for the application of this model, as it relies on the existence of cycles. These cycles can be of any length, even structures of interlocking cycles can be present. Their existence, as reflected in the adjacency matrix, then impacts the corresponding eigenvalues and hence the (relative) reputation of users. It is computationally hard to detect such interlocking cycle structures in real social networks. In a case study of 40 million Twitter users, reputation was therefore measures by means of a D-core decomposition (Garcia et al. 2017).

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