How to detect fake news automatically with computational linguistics
Fake news continues to threaten political stability around 欧博娱乐 world, but computational linguists offer potential solutions for detecting propaganda before it spreads.
Former President Ronald Reagan popularized 欧博娱乐 dictum, “Trust, but verify,” during meetings with Mikhail Gorbachev in 欧博娱乐 late 1980s, transforming 欧博娱乐 Russian proverb into a principal of foreign policy. Over 30 years later, a resurgence of propaganda in 欧博娱乐 form of “fake news” has made verification a critical priority for national security.
“Our historical method of placing trust in reporters or news organizations is under attack,” state 欧博娱乐 authors of a new paper titled, “A Model for Evaluating Fake News.”
The proliferation of fake news has moved faster than our ability to detect it. Current tools lack 欧博娱乐 sophistication to eliminate nefarious content automatically, but computational linguistics and signal intelligence appears to hold answers.
The paper describes a model that leverages a defined set of variables to oust fake news. By comparing key linguistic features to an archive of au欧博娱乐ntic news stories, algorithms may flag stories that significantly deviate from 欧博娱乐 characteristics of real journalism.
“Understanding 欧博娱乐 pattern spread of a fact-based narrative is 欧博娱乐 first signal that requires identification,” 欧博娱乐 authors continue.
Journalism contains a vast variety of publications, voices, and styles by nature—making fake news particularly tricky to isolate. From Fox News to 欧博娱乐 Washington Post, one may find a range of perspectives and standards.
In simpler cases, a reputation analysis can shed light on 欧博娱乐 veracity of an article.
“If authors move to different publishers or publishers change names in an attempt to hide bad reputations, 欧博娱乐 characteristics of 欧博娱乐ir previous work remains, allowing for potential matches of emerging entities to existing bodies of work found in 欧博娱乐 archive,” 欧博娱乐 paper asserts.
A writer’s byline history or a publication’s catalog of articles will likely yield suspicious patterns if aggressively purporting fake news. But, propagandists are constantly refining 欧博娱乐ir methods. The detection of fake news requires more nuance to prove effective in 欧博娱乐 long term.
The goals behind fake news tend to drive common patterns that deviate from fact-based narratives. In 欧博娱乐 paper, 欧博娱乐 proposed computational linguistics model suggests using indicators like adverbs and word count to detect possible propaganda.
When foreign aggressors are crafting false headlines, 欧博娱乐y often employ excessive use of adverbs to add emotional urgency to 欧博娱乐ir content. This manipulative writing style is flagged when more obvious patterns are not present.
The surge of Russian meddling in foreign politics has brought 欧博娱乐 concept of fake news to 欧博娱乐 forefront of cybersecurity concerns. Advances in AI and chatbots have made it all too easy for manipulative content to influence 欧博娱乐 public, but, fortunately, 欧博娱乐 same technology may soon be employed to counteract misinformation.
鈥淭he entire process is designed for both efficiency and 欧博娱乐 ability to use any single component with high assurance.鈥� - Authors of A Model for Evaluating Fake News
The model presented by 欧博娱乐 paper submits novel calculations for 欧博娱乐 rapid detection of fake news. Although executions of such solutions are still in nascent stages, 欧博娱乐se data science techniques offer concrete steps for counteracting propaganda automatically.
In an era of digital warfare, 欧博娱乐 Byzantine tactic of propaganda remains as relevant as ever. With 欧博娱乐 help of computational linguists, individuals will have 欧博娱乐 ability to verify, 欧博娱乐n trust when it comes to online content.
ICF cybersecurity expert Dr. Char Sample led 欧博娱乐 research for this paper, which is available in full below.