Novel method can detect dishonest tweets online
Kim-Kwang Raymond Choo, associate professor of information systems and cybersecurity at University of Texas at San Antonio (UTSA) developed a method for detecting people dishonestly posting online comments, reviews or tweets across multiple accounts.tech Updated: Oct 24, 2016 12:49 IST
A team of US researchers has developed a unique method that, after analysing online comments or tweets, can find dishonesty levels behind posting those thoughts - a practice also called ‘astroturfing’.
Astroturfing is the deceptive practice of presenting an orchestrated marketing or public relations campaign in the guise of unsolicited comments from members of the public.
Former US President George W Bush and current US presidential candidates Hillary Clinton and Donald Trump have been accused of ‘astroturfing’ to claim widespread enthusiasm for their platforms.
Kim-Kwang Raymond Choo, associate professor of information systems and cybersecurity at University of Texas at San Antonio (UTSA) developed a method for detecting people dishonestly posting online comments, reviews or tweets across multiple accounts.
“Astroturfing is legal, but it’s questionable ethically. As long as social media has been popular, this has existed,” said Choo.
The method analyses multiple writing samples. Choo and his collaborators found that it’s challenging for authors to completely conceal their writing style in their text.
Based on word choice, punctuation and context, the method is able to detect whether one person or multiple people are responsible for the samples.
Choo and his co-authors used writing samples from the most prolific online commentators on various news websites.
They discovered that many people espousing their opinions online were actually all linked to a few singular writers with multiple accounts.
The practice has been used by businesses to manipulate social media users or online shoppers, by having one paid associate post false reviews on web sites about products for sale.
It is also used on social media wherein ‘astroturfers’ create several false accounts to espouse opinions, creating the illusion of a consensus when actually one person is pretending to be many.
“Businesses can use this to encourage support for their products or services or to sabotage other competing companies by spreading negative opinions through false identities,” Choo added in a university statement.
Choo is now looking into whether the algorithm can be used to prevent plagiarism and contract cheating.
“In addition to raising public awareness of the problem, we hope to develop tools to detect astroturfers so that social media users can make informed choices and resist online social manipulation and propaganda,” Choo noted.