The Role of Trends in Evolving Networks
Osnat Mokryn, Marcel Blattner, Yuval Shavitt

TL;DR
This paper extends the preferential attachment model by incorporating trends, explaining properties like clustering and late node growth in evolving networks, and demonstrating its relevance to real-world social, economic, and online networks.
Contribution
It introduces a trend-based extension to the PA model, capturing additional network properties and explaining the dynamic importance of nodes in evolving networks.
Findings
Trending nodes can become central and form new clusters.
Networks exhibit a mix of static power-law and dynamic trend-driven parts.
Trend influence varies with network age and product susceptibility.
Abstract
Modeling complex networks has been the focus of much research for over a decade. Preferential attachment (PA) is considered a common explanation to the self organization of evolving networks, suggesting that new nodes prefer to attach to more popular nodes. The PA model results in broad degree distributions, found in many networks, but cannot explain other common properties such as: The growth of nodes arriving late and Clustering (community structure). Here we show that when the tendency of networks to adhere to trends is incorporated into the PA model, it can produce networks with such properties. Namely, in trending networks, newly arriving nodes may become central at random, forming new clusters. In particular, we show that when the network is young it is more susceptible to trends, but even older networks may have trendy new nodes that become central in their structure.…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Evolutionary Game Theory and Cooperation
