title: The Role of Temporal Trends in Growing Networks.
abstract: The rich get richer principle, manifested by the Preferential attachment (PA) mechanism, is widely considered one of the major factors in the growth of real-world networks. PA stipulates that popular nodes are bound to be more attractive than less popular nodes; for example, highly cited papers are more likely to garner further citations. However, it overlooks the transient nature of popularity, which is often governed by trends. Here, we show that in a wide range of real-world networks the recent popularity of a node, i.e., the extent by which it accumulated links recently, significantly influences its attractiveness and ability to accumulate further links. We proceed to model this observation with a natural extension to PA, named Trending Preferential Attachment (TPA), in which edges become less influential as they age. TPA quantitatively parametrizes a fundamental network property, namely the network's tendency to trends. Through TPA, we find that real-world networks tend to be moderately to highly trendy. Networks are characterized by different susceptibilities to trends, which determine their structure to a large extent. Trendy networks display complex structural traits, such as modular community structure and degree-assortativity, occurring regularly in real-world networks. In summary, this work addresses an inherent trait of complex networks, which greatly affects their growth and structure, and develops a unified model to address its interaction with preferential attachment.
authors.affiliation: Information and Knowledge Management Dept., University of Haifa, Haifa, Israel.
authors.forename: Osnat
authors.initials: O
authors.lastname: Mokryn
authors.affiliation: The Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.|Laboratory for Web Science, University of Applied Sciences (FFHS), & Tamedia Digital Analytics, Tamedia Zurich, Switzerland.
authors.forename: Allon
authors.initials: A
authors.lastname: Wagner
authors.affiliation: Laboratory for Web Science, University of Applied Sciences (FFHS), & Tamedia Digital Analytics, Tamedia Zurich, Switzerland.
authors.forename: Marcel
authors.initials: M
authors.lastname: Blattner
authors.affiliation: The Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.|The Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
authors.affiliation: School of Electrical Engineering, Tel-Aviv University, Tel-Aviv, Israel.
authors.forename: Yuval
authors.initials: Y
authors.lastname: Shavitt
mesh_terms: D015706:Bibliometrics; D006801:Humans; D008962:Models, Theoretical; D060756:Social Networking