{"id":857,"date":"2023-06-25T01:31:15","date_gmt":"2023-06-25T01:31:15","guid":{"rendered":"https:\/\/zli.one\/?p=857"},"modified":"2023-06-25T01:33:09","modified_gmt":"2023-06-25T01:33:09","slug":"leveraging-natural-language-processing-for-fake-news-detection","status":"publish","type":"post","link":"https:\/\/zli.one\/?p=857","title":{"rendered":"Leveraging Natural Language Processing for Fake News Detection"},"content":{"rendered":"\n<div class=\"wp-block-cover alignfull is-light\" style=\"min-height:464px;aspect-ratio:unset;\"><span aria-hidden=\"true\" class=\"wp-block-cover__background has-background-dim-100 has-background-dim\" style=\"background-color:#ffffff\"><\/span><div class=\"wp-block-cover__inner-container is-layout-flow wp-block-cover-is-layout-flow\">\n<div class=\"wp-block-media-text alignwide is-stacked-on-mobile is-vertically-aligned-center is-image-fill\" style=\"grid-template-columns:56% auto\"><figure class=\"wp-block-media-text__media\" style=\"background-image:url(https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/istockphoto-491732089-170667a.jpg);background-position:58% 56%\"><img loading=\"lazy\" decoding=\"async\" width=\"343\" height=\"499\" src=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/istockphoto-491732089-170667a.jpg\" alt=\"\" class=\"wp-image-859 size-full\" srcset=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/istockphoto-491732089-170667a.jpg 343w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/istockphoto-491732089-170667a-206x300.jpg 206w\" sizes=\"auto, (max-width: 343px) 100vw, 343px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<h2 class=\"wp-block-heading has-text-color\" style=\"color:#000000;font-size:32px\"><strong>Fake News Detection<\/strong><\/h2>\n\n\n\n<p class=\"has-text-color wp-block-paragraph\" style=\"color:#000000;font-size:17px\">This study proposes an effective approach for fake news de- tection leveraging a fine-tuned BERT model. By adapting BERT\u2019s language understanding capabilities, we achieved improved performance in identifying fake news articles. Our approach achieved better result comparing to traditional machine learning methods like CNN and base BERT. This project underscores the potential of BERT models in address- ing the fake news issue and suggests new opportunities for further research in this field.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-fill\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/CS263_Final_Report.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">Paper<\/a><\/div>\n\n\n\n<div class=\"wp-block-button is-style-fill\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/github.com\/yw509\/COM_SCI_263_Final\/tree\/main\">GitHub<\/a><\/div>\n<\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Data Set<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-1024x367.png\" alt=\"\" class=\"wp-image-863\" width=\"1239\" height=\"444\" srcset=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-1024x367.png 1024w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-300x107.png 300w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-768x275.png 768w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-1536x550.png 1536w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-2048x734.png 2048w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.27.43-PM-496x178.png 496w\" sizes=\"auto, (max-width: 1239px) 100vw, 1239px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>WorkFlow<\/strong><\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Picture1.png\" alt=\"\" class=\"wp-image-860\" width=\"1206\" height=\"350\" srcset=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Picture1.png 960w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Picture1-300x87.png 300w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Picture1-768x223.png 768w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Picture1-496x144.png 496w\" sizes=\"auto, (max-width: 1206px) 100vw, 1206px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\"><strong>Result<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"778\" height=\"263\" src=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.29.57-PM.png\" alt=\"\" class=\"wp-image-864\" srcset=\"https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.29.57-PM.png 778w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.29.57-PM-300x101.png 300w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.29.57-PM-768x260.png 768w, https:\/\/zli.one\/wp-content\/uploads\/2023\/06\/Screenshot-2023-06-24-at-6.29.57-PM-496x168.png 496w\" sizes=\"auto, (max-width: 778px) 100vw, 778px\" \/><\/figure>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\"><\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Set WorkFlow Result<\/p>\n","protected":false},"author":1,"featured_media":865,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-857","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-projects"],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/posts\/857","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/zli.one\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=857"}],"version-history":[{"count":3,"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/posts\/857\/revisions"}],"predecessor-version":[{"id":868,"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/posts\/857\/revisions\/868"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/zli.one\/index.php?rest_route=\/wp\/v2\/media\/865"}],"wp:attachment":[{"href":"https:\/\/zli.one\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=857"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/zli.one\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=857"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/zli.one\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=857"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}