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Here we define a structural importance metric\u2014which we denote as <jats:inline-formula><jats:alternatives><jats:tex-math>$l_{e}$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:msub>\n                    <mml:mi>l<\/mml:mi>\n                    <mml:mi>e<\/mml:mi>\n                  <\/mml:msub>\n                <\/mml:math><\/jats:alternatives><\/jats:inline-formula>\u2014for the edges of a network. The metric is based on perturbing the adjacency matrix and observing the resultant change in its largest eigenvalues. We then propose a model of network evolution where this metric controls the probabilities of subsequent edge changes. We show using synthetic data how the parameters of the model are related to the capability of predicting whether an edge will change from its value of <jats:inline-formula><jats:alternatives><jats:tex-math>$l_{e}$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:msub>\n                    <mml:mi>l<\/mml:mi>\n                    <mml:mi>e<\/mml:mi>\n                  <\/mml:msub>\n                <\/mml:math><\/jats:alternatives><\/jats:inline-formula>. We then estimate the model parameters associated with five real financial and social networks, and we study their predictability. These methods have applications in financial regulation whereby it is important to understand how individual changes to financial networks will impact their global behaviour. It also provides fundamental insights into spectral predictability in networks, and it demonstrates how spectral perturbations can be a useful tool in understanding the interplay between micro and macro features of networks.<\/jats:p>","DOI":"10.1140\/epjds\/s13688-021-00279-6","type":"journal-article","created":{"date-parts":[[2021,5,8]],"date-time":"2021-05-08T09:05:19Z","timestamp":1620464719000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Evaluating structural edge importance in temporal networks"],"prefix":"10.1140","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5702-8504","authenticated-orcid":false,"given":"Isobel E.","family":"Seabrook","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Barucca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabio","family":"Caccioli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,5,8]]},"reference":[{"key":"279_CR1","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.1016\/j.jedc.2007.01.014","volume":"31","author":"E Nier","year":"2007","unstructured":"Nier E, Yang J, Yorulmazer T, Alentorn A (2007) Network models and financial stability. 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