Researchers find new way to amplify trustworthy news content on social
media without shielding bias

Date:
February 3, 2022
Source:
University of South Florida (USF Innovation)
Summary:
Social media sites continue to amplify misinformation and conspiracy
theories. To address this concern, an interdisciplinary team of
computer scientists, physicists and social scientists has found a
solution to ensure social media users are exposed to more reliable
news sources.



FULL STORY ========================================================================== Social media sites continue to amplify misinformation and conspiracy
theories.

To address this concern, an interdisciplinary team of computer scientists, physicists and social scientists led by the University of South Florida
(USF) has found a solution to ensure social media users are exposed to
more reliable news sources.


==========================================================================
In their study published in the journal Nature Human Behaviour, the
researchers focused on the recommendation algorithm that is used by
social media platforms to prioritize content displayed to users. Rather
than measuring engagement based on the number of users and pageviews,
the researchers looked at what content gets amplified on a newsfeed,
focusing on a news source's reliability score and the political diversity
of their audience.

"Low-quality content is engaging because it conforms to what we
already know and like, regardless of whether it is accurate or not,"
said Giovanni Luca Ciampaglia, assistant professor of computer science
and engineering at USF. "As a result, misinformation and conspiracy
theories often go viral within like- minded audiences. The algorithm
ends up picking the wrong signal and keeps promoting it further. To
break this cycle, one should look for content that is engaging, but
for a diverse audience, not for a like-minded one." In collaboration
with researchers at Indiana University and Dartmouth College, the team
created a new algorithm using data on the web traffic and self- reported partisanship of 6,890 individuals who reflect the diversity of the United States in sex, race and political affiliation. The data was provided
by online polling company YouGov. They also reviewed the reliability
scores of 3,765 news sources based on the NewGuard Reliability Index,
which rates news sources on several journalistic criteria, such as
editorial responsibility, accountability and financial transparency.

They found that incorporating the partisan diversity of a news audience
can increase the reliability of recommended sources while still providing
users with relevant recommendations. Since the algorithm isn't exclusively based on engagement or popularity, it is still able to promote reliable sources, regardless of their partisanship.

"This is especially welcome news for social media platforms, especially
since they have been reluctant of introducing changes to their algorithms
for fear of criticism about partisan bias," said co-author Filippo
Menczer, distinguished Luddy professor of informatics and computer
science at Indiana University.

Researchers say that platforms would easily be able to include audience diversity into their own recommendation algorithms because diversity
measures can be derived from engagement data, and platforms already
log this type of data whenever users click "like" or share something
on a newsfeed. Ciampaglia and his colleagues propose social media
platforms adopt this new strategy in order to help prevent the spread
of misinformation.

special promotion Explore the latest scientific research on sleep and
dreams in this free online course from New Scientist -- Sign_up_now_>>> ========================================================================== Story Source: Materials provided by University_of_South_Florida_(USF_Innovation). Note: Content may be edited
for style and length.


========================================================================== Journal Reference:
1. Saumya Bhadani, Shun Yamaya, Alessandro Flammini, Filippo Menczer,
Giovanni Luca Ciampaglia, Brendan Nyhan. Political audience
diversity and news reliability in algorithmic ranking. Nature
Human Behaviour, 2022; DOI: 10.1038/s41562-021-01276-5 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220203122858.htm

--- up 8 weeks, 5 days, 7 hours, 13 minutes
* Origin: -=> Castle Rock BBS <=- Now Husky HPT Powered! (1:317/3)