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We highlight several recent approaches in modeling higher-order temporal interaction and bring them together under the umbrella of event graphs. Through examples, we demonstrate how event graphs can be used to understand the higher-order topological-temporal structure of temporal networks and capture properties of the network that are unobservable when considering either a static (or time-aggregated) model. We introduce new algorithms for temporal motif enumeration and provide a novel analysis of the communicability centrality for temporal networks. Furthermore, we show that by modeling a temporal network as an event graph our analysis extends easily to non-dyadic interactions, known as hyper-events.<\/jats:p>","DOI":"10.1142\/s0219525919500061","type":"journal-article","created":{"date-parts":[[2019,8,21]],"date-time":"2019-08-21T07:49:56Z","timestamp":1566373796000},"page":"1950006","source":"Crossref","is-referenced-by-count":4,"title":["EVENT GRAPHS: ADVANCES AND APPLICATIONS OF SECOND-ORDER TIME-UNFOLDED TEMPORAL NETWORK MODELS"],"prefix":"10.1142","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1581-9671","authenticated-orcid":false,"given":"ANDREW","family":"MELLOR","sequence":"first","affiliation":[{"name":"Mathematical Institute, University of Oxford, Woodstock Road, OX2 6GG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2019,8,26]]},"reference":[{"issue":"2007","key":"S0219525919500061BIB001","first-page":"450","volume":"8","author":"Alon U","journal-title":"Nat. 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