{"id":3879,"date":"2022-01-21T10:45:24","date_gmt":"2022-01-21T09:45:24","guid":{"rendered":"https:\/\/datascience.unifi.it\/?post_type=tribe_events&#038;p=3879"},"modified":"2022-03-08T12:41:10","modified_gmt":"2022-03-08T11:41:10","slug":"13th-seminar-of-the-d2-seminar-series-florence-center-for-data-science","status":"publish","type":"tribe_events","link":"https:\/\/datascience.unifi.it\/index.php\/event\/13th-seminar-of-the-d2-seminar-series-florence-center-for-data-science\/","title":{"rendered":"13th Seminar of the \u201cD2 Seminar Series\u201d \u2013 Florence Center for Data Science"},"content":{"rendered":"<p>The Florence Center for Data Science is happy to present the 13th Seminar of the \u201cD2 Seminar Series\u201d launched by the FDS. The Seminar will be held online Friday <strong>11th <\/strong>of\u00a0<b>March <\/b>2021, from\u00a0<strong>2-3 pm.<\/strong><\/p>\n<p>The seminar on\u00a0<i>\u201c<\/i>\u00a0<i>Paths and flows for centrality measures in networks\u201d <\/i>will be held by Daniela Bubboloni from the Department of Mathematics and Computer Science \u201cUlisse Dini\u201d of the University of Florence.<\/p>\n<p>Register in advance for this webinar:<br \/>\n<a href=\"https:\/\/us02web.zoom.us\/webinar\/register\/WN_IeBS9Nx7Tm2Cn7moqPpFUQ\">https:\/\/us02web.zoom.us\/webinar\/register\/WN_KFoLkeSfT3-kzWLK2mwHPA<\/a><\/p>\n<p>After registering, you will receive a confirmation email containing information about joining the webinar.<\/p>\n<p>\u2014\u2014\u2014\u2014\u2014\u2014\u2014<\/p>\n<p><strong>Speaker<\/strong><span style=\"font-family: monospace;\">:\u00a0Daniela Bubboloni &#8211; Department of Mathematics and Computer Science \u201cUlisse Dini\u201d, University of Florence<\/span><\/p>\n<p><span style=\"font-family: monospace;\"><strong>Title<\/strong>:\u00a0Paths and flows for centrality measures in networks<\/span><\/p>\n<p><span style=\"font-family: monospace;\"><strong>Abstract<\/strong>:\u00a0Consider the number of paths that must pass through a subset X of vertices of a capacitated network N in a maximum sequence of arc-disjoint paths connecting two vertices y and z. Consider then the difference between the maximum flow value from y to z in N and the maximum flow value from y to z in the network obtained by N by setting to zero the capacities of all the arcs incident to X. When X is a singleton, those quantities are involved in defining and computing the flow betweenness centrality and are commonly identified without any rigorous proof justifying the identification. That surprising gap in the literature is the starting point of our research. On the basis of a deep analysis of the interplay between paths and flows, we prove that, when X is a singleton, those quantities coincide. On the other hand, when X has at least two elements, those quantities may be different from each other. By means of the considered quantities, two conceptually different group centrality measures, respectively based on paths and flows, can be naturally defined. Such group centrality measures both extend the flow betweenness centrality to groups of vertices and satisfy a desirable form of monotonicity.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Florence Center for Data Science is happy to present the 13th Seminar of the \u201cD2 Seminar Series\u201d launched by the FDS. The Seminar will be held online Friday 11th &#8230;<\/p>\n","protected":false},"author":1,"featured_media":3301,"template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[35],"class_list":["post-3879","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-seminar","cat_seminar"],"_links":{"self":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/3879","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":4,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/3879\/revisions"}],"predecessor-version":[{"id":4056,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/3879\/revisions\/4056"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/media\/3301"}],"wp:attachment":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/media?parent=3879"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tags?post=3879"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events_cat?post=3879"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}