{"id":8294,"date":"2023-09-29T14:31:30","date_gmt":"2023-09-29T14:31:30","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/?post_type=chapter&#038;p=8294"},"modified":"2024-10-18T20:58:08","modified_gmt":"2024-10-18T20:58:08","slug":"graph-theory-basics-apply-it-2","status":"web-only","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/chapter\/graph-theory-basics-apply-it-2\/","title":{"raw":"Graph Theory Basics: Apply It 2","rendered":"Graph Theory Basics: Apply It 2"},"content":{"raw":"<h2>Graphs of Social Interactions<\/h2>\r\n<p>Geographical maps are just one of many real-world scenarios which graphs can depict. Any scenario in which objects are connected to each other can be represented with a graph, and the connections don\u2019t have to be physical. Just think about all the connections you have to people around the world through social media! Who is in your network of Twitter followers? Whose Snapchat network are you connected to?<\/p>\r\n<section class=\"textbox tryIt\">\r\n<p>[ohm2_question hide_question_numbers=1]13899[\/ohm2_question]<\/p>\r\n<\/section>\r\n<section class=\"textbox tryIt\">\r\n<p>[ohm2_question hide_question_numbers=1]13900[\/ohm2_question]<\/p>\r\n<\/section>\r\n<section class=\"textbox connectIt\">\r\n<header>\r\n<h4 class=\"os-title\" data-type=\"title\"><span class=\"os-title-label\">WHO KNEW? <\/span>Using Graph Theory to Reduce Internet Fraud<\/h4>\r\n<\/header>\r\n<section>\r\n<div class=\"os-note-body\">\r\n<p id=\"para-00033\">Could graphs be used to reduce Internet fraud? At least one researcher thinks so. Graph theory is used every day to analyze our behavior, particularly on social network sites. Alex Buetel, a computer scientist from Carnegie Mellon University in Pittsburgh, Pennsylvania, published a research paper in 2016 that discussed the possibilities of distinguishing the normal interactions from those that might be fraudulent using graph theory. Buetel wrote, \u201cTo more effectively model and detect abnormal behavior, we model\u00a0<em data-effect=\"italics\">how<\/em>\u00a0fraudsters work, catching previously undetected fraud on Facebook, Twitter, and Tencent Weibo and improving classification accuracy by up to [latex]68\\%[\/latex].\u201d In the same paper, the researcher discusses how similar techniques can be used to model many other applications and even, \u201cpredict\u00a0<em data-effect=\"italics\">why<\/em>\u00a0you like a particular movie.\u201d[footnote] Alex Beutel, \"User Behavior Modeling with Large-Scale Graph Analysis,\" http:\/\/reports-archive.adm.cs.cmu.edu\/anon\/2016\/CMU-CS-16-105.pdf , May 2016, CMU-CS-16-105, Computer Science Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA[\/footnote]<\/p>\r\n<\/div>\r\n<\/section>\r\n<\/section>","rendered":"<h2>Graphs of Social Interactions<\/h2>\n<p>Geographical maps are just one of many real-world scenarios which graphs can depict. Any scenario in which objects are connected to each other can be represented with a graph, and the connections don\u2019t have to be physical. Just think about all the connections you have to people around the world through social media! Who is in your network of Twitter followers? Whose Snapchat network are you connected to?<\/p>\n<section class=\"textbox tryIt\">\n<iframe loading=\"lazy\" id=\"ohm13899\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=13899&theme=lumen&iframe_resize_id=ohm13899&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><br \/>\n<\/section>\n<section class=\"textbox tryIt\">\n<iframe loading=\"lazy\" id=\"ohm13900\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=13900&theme=lumen&iframe_resize_id=ohm13900&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><br \/>\n<\/section>\n<section class=\"textbox connectIt\">\n<header>\n<h4 class=\"os-title\" data-type=\"title\"><span class=\"os-title-label\">WHO KNEW? <\/span>Using Graph Theory to Reduce Internet Fraud<\/h4>\n<\/header>\n<section>\n<div class=\"os-note-body\">\n<p id=\"para-00033\">Could graphs be used to reduce Internet fraud? At least one researcher thinks so. Graph theory is used every day to analyze our behavior, particularly on social network sites. Alex Buetel, a computer scientist from Carnegie Mellon University in Pittsburgh, Pennsylvania, published a research paper in 2016 that discussed the possibilities of distinguishing the normal interactions from those that might be fraudulent using graph theory. Buetel wrote, \u201cTo more effectively model and detect abnormal behavior, we model\u00a0<em data-effect=\"italics\">how<\/em>\u00a0fraudsters work, catching previously undetected fraud on Facebook, Twitter, and Tencent Weibo and improving classification accuracy by up to [latex]68\\%[\/latex].\u201d In the same paper, the researcher discusses how similar techniques can be used to model many other applications and even, \u201cpredict\u00a0<em data-effect=\"italics\">why<\/em>\u00a0you like a particular movie.\u201d<a class=\"footnote\" title=\"Alex Beutel, &quot;User Behavior Modeling with Large-Scale Graph Analysis,&quot; http:\/\/reports-archive.adm.cs.cmu.edu\/anon\/2016\/CMU-CS-16-105.pdf , May 2016, CMU-CS-16-105, Computer Science Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA\" id=\"return-footnote-8294-1\" href=\"#footnote-8294-1\" aria-label=\"Footnote 1\"><sup class=\"footnote\">[1]<\/sup><\/a><\/p>\n<\/div>\n<\/section>\n<\/section>\n<hr class=\"before-footnotes clear\" \/><div class=\"footnotes\"><ol><li id=\"footnote-8294-1\"> Alex Beutel, \"User Behavior Modeling with Large-Scale Graph Analysis,\" http:\/\/reports-archive.adm.cs.cmu.edu\/anon\/2016\/CMU-CS-16-105.pdf , May 2016, CMU-CS-16-105, Computer Science Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA <a href=\"#return-footnote-8294-1\" class=\"return-footnote\" aria-label=\"Return to footnote 1\">&crarr;<\/a><\/li><\/ol><\/div>","protected":false},"author":15,"menu_order":7,"template":"","meta":{"_candela_citation":"[{\"type\":\"cc-attribution\",\"description\":\"Contemporary Mathematics\",\"author\":\"Donna Kirk\",\"organization\":\"OpenStax\",\"url\":\"https:\/\/openstax.org\/books\/contemporary-mathematics\/pages\/12-1-graph-basics#fig-00013\",\"project\":\"12.1 Graph Basics\",\"license\":\"cc-by\",\"license_terms\":\"Access for free at https:\/\/openstax.org\/books\/contemporary-mathematics\/pages\/1-introduction\"}]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":75,"module-header":"apply_it","content_attributions":[{"type":"cc-attribution","description":"Contemporary Mathematics","author":"Donna Kirk","organization":"OpenStax","url":"https:\/\/openstax.org\/books\/contemporary-mathematics\/pages\/12-1-graph-basics#fig-00013","project":"12.1 Graph Basics","license":"cc-by","license_terms":"Access for free at https:\/\/openstax.org\/books\/contemporary-mathematics\/pages\/1-introduction"}],"internal_book_links":[],"video_content":null,"cc_video_embed_content":{"cc_scripts":"","media_targets":[]},"try_it_collection":null,"_links":{"self":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8294"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/users\/15"}],"version-history":[{"count":9,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8294\/revisions"}],"predecessor-version":[{"id":14835,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8294\/revisions\/14835"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/parts\/75"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8294\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/media?parent=8294"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapter-type?post=8294"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/contributor?post=8294"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/license?post=8294"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}