Distinct types of eigenvector localization in networks
نویسندگان
چکیده
منابع مشابه
Distinct types of eigenvector localization in networks
The spectral properties of the adjacency matrix provide a trove of information about the structure and function of complex networks. In particular, the largest eigenvalue and its associated principal eigenvector are crucial in the understanding of nodes' centrality and the unfolding of dynamical processes. Here we show that two distinct types of localization of the principal eigenvector may occ...
متن کاملthe norms of localization in translating persian multimodal texts: the case of videogame demos
abstract هنجارهای بومی سازی در ترجمه متون چندوجهی فارسی:مورد دموهای بازیهای کامپیوتری چکیده اهداف عمده مطالعه حاضر به سه دسته تقسیم میشوند: 1) بررسی مشکلات احتمالی ترجمه دموهای (فیلمهای) بازیهای کامپیوتری،2) تعیین هنجارهای بومی سازی در ترجمه دموهای (فیلمهای) بازیهای کامپیوتری و 3) تعیین ایدئولوژیهایی که این هنجارها در جامعه نشان میدهند. به این منظور، ابتدا، مجموعه ای ازدموهای (فیلمهای) ب...
15 صفحه اولEigenvector centrality of nodes in multiplex networks
We extend the concept of eigenvector centrality to multiplex networks, and introduce several alternative parameters that quantify the importance of nodes in a multi-layered networked system, including the definition of vectorial-type centralities. In addition, we rigorously show that, under reasonable conditions, such centrality measures exist and are unique. Computer experiments and simulation...
متن کاملEigenvector localization in real networks and its implications for epidemic spreading
The spectral properties of the adjacency matrix, in particular its largest eigenvalue and the associated principal eigenvector, dominate many structural and dynamical properties of complex networks. Here we focus on the localization properties of the principal eigenvector in real networks. We show that in most cases it is either localized on the star defined by the node with largest degree (hub...
متن کاملEigenvector Localization as a Tool to Study Small Communities in Online Social Networks
We present and discuss a mathematical procedure for identification of small “communities” or segments within large bipartite networks. The procedure is based on spectral analysis of the matrix encoding network structure. The principal tool here is localization of eigenvectors of the matrix, by means of which the relevant network segments become visible. We exemplified our approach by analyzing ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2016
ISSN: 2045-2322
DOI: 10.1038/srep18847