{"id":3376,"date":"2018-08-23T11:53:32","date_gmt":"2018-08-23T06:23:32","guid":{"rendered":"https:\/\/www.oyspa.com\/blog\/?p=3376"},"modified":"2018-08-23T11:53:32","modified_gmt":"2018-08-23T06:23:32","slug":"fake-news-major-concern-today","status":"publish","type":"post","link":"https:\/\/www.oyspa.com\/blog\/news\/fake-news-major-concern-today\/","title":{"rendered":"Fake news Detector : Fake news is Major concern today"},"content":{"rendered":"

Fake news<\/strong>\u00a0is a type of yellow journalism<\/strong> that has become a major concern today. So much so that it was even termed ‘word of the year’ in 2017.<\/strong>
\nIn an attempt to deal with the issue, researchers have come up with an\u00a0algorithm-based system that identifies telltale linguistic cues in fake news stories and could provide news aggregator and social media sites like Google News with a new weapon in the fight against misinformation.
\nThe University of Michigan researchers have claimed that the system is comparable to, and sometimes better than\u00a0humans at correctly identifying fake news stories.
\nIn a recent study, it successfully found fakes up to 76 per cent of the time, compared to a\u00a0human<\/strong>\u00a0success rate of 70 per cent. In addition, their linguistic analysis approach could be used to identify fake news articles that are too new to be debunked by cross-referencing their facts with other stories.
\nRada Mihalcea, one of the researchers behind the project, said that an automated solution could be an important tool for sites that are struggling to deal with an onslaught of fake news stories, often created to generate clicks or to manipulate public opinion.
\nCatching fake stories before they have real consequences can be difficult, as the aggregator and social media sites today rely heavily on\u00a0human\u00a0editors who often can’t keep up with the influx of news. In addition, current debunking techniques often depend on external verification of facts, which can be difficult with the newest stories. Often, by the time a story is proven a fake, the damage has already been done.
\nThe linguistic analysis takes a different approach, analyzing quantifiable attributes like grammatical structure, word choice, punctuation and complexity. It works faster than\u00a0humans and it can be used with a variety of different news types.
\n“You can imagine any number of applications for this on the front or back end of a news or social media site,” Mihalcea said.
\nExplaining the use of the system she added, “It could provide users with an estimate of the trustworthiness of individual stories or a whole news site. Or it could be the first line of defence on the back end of a news site, flagging suspicious stories for further review. A 76 per cent success rate leaves a fairly large margin of error, but it can still provide valuable insight when it’s used alongside\u00a0humans.”
\nLinguistic\u00a0algorithms that analyse written speech are fairly common today. But according to Mihalcea the challenge of building a fake news detector lies not in building the\u00a0algorithm\u00a0itself, but in finding the right data with which to train that\u00a0algorithm.
\nFake news\u00a0appears and disappears quickly, which makes it difficult to collect. It also comes in many genres, further complicating the collection process. Satirical news, for example, is easy to collect, but its use of irony and absurdity makes it less useful for training an\u00a0algorithm\u00a0to detect fake news that’s meant to mislead.
\nUltimately, Mihalcea’s team created its own data, crowd-sourcing an online team that reverse-engineered verified genuine news stories into fakes. This is how most actual fake news is created, Mihalcea said, by individuals who quickly write them in return for a monetary reward.
\nStudy participants, recruited with the help of Amazon Mechanical Turk, were paid to turn short, actual news stories into similar but fake news items, mimicking the journalistic style of the articles. At the end of the process, the research team had a dataset of 500 real and fake news stories.
\nThey then fed these labelled pairs of stories to an\u00a0algorithm\u00a0that performed a linguistic analysis, teaching itself distinguish between real and fake news. Finally, the team turned the\u00a0algorithms into a dataset of real and fake news pulled directly from the web, netting the 76 per cent success rate.
\nThe details of the new system and the dataset that the team used to build it are freely available, and Mihalcea says they could be used by news sites or other entities to build their own fake news detection systems. She says that future systems could be further honed by incorporating metadata such as the links and comments associated with a given online news item.
\nA paper detailing the system will be presented on August 24th at the 27th International Conference on Computational Linguistics in Santa Fe.<\/p>\n","protected":false},"excerpt":{"rendered":"

Fake news\u00a0is a type of yellow journalism that has become a major concern today. So much so that it was […]<\/p>\n","protected":false},"author":11,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[4,99],"tags":[],"class_list":["post-3376","post","type-post","status-publish","format-standard","hentry","category-news","category-devlopment"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/paZdga-Ss","jetpack-related-posts":[],"jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/posts\/3376","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/comments?post=3376"}],"version-history":[{"count":1,"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/posts\/3376\/revisions"}],"predecessor-version":[{"id":3378,"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/posts\/3376\/revisions\/3378"}],"wp:attachment":[{"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/media?parent=3376"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/categories?post=3376"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.oyspa.com\/blog\/wp-json\/wp\/v2\/tags?post=3376"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}