Sharing Articles On Social Media Sans Reading Make Us Think We’re Now Experts
New York, Aug 31: Sharing articles on Facebook or Twitter, even when we haven’t read them, can lead us to believe we are experts on a particular topic and this can be a risky situation, new research has revealed.
Sharing news articles with friends and followers on social media can prompt people to think they know more about the articles’ topics than they actually do, according to a new study from researchers at The University of Texas at Austin in the US.
“When people feel they’re more knowledgeable, they’re more likely to make riskier decisions,” said assistant professor Adrian Ward.
The study, published in the Journal of Consumer Psychology, said that social media sharers believe that they are knowledgeable about the content they share, even if they have not read it or have only glanced at a headline.
“Sharing can create this rise in confidence because by putting information online, sharers publicly commit to an expert identity. Doing so shapes their sense of self, helping them to feel just as knowledgeable as their post makes them seem,” the findings showed.
To reach this conslusion, Susan M Broniarczyk and Ward Broniarczyk conducted several studies.
They found that people internalise their sharing into the self-concept, which leads them to believe they are as knowledgeable as their posts make them appear.
“Participants thought they knew more when their sharing publicly committed them to an expert identity: when sharing under their own identity versus an alias, when sharing with friends versus strangers, and when they had free choice in choosing what to share,” said the study.
The research suggests there’s merit to social media companies that have piloted ways to encourage people to read articles before sharing.
“If people feel more knowledgeable on a topic, they also feel they maybe don’t need to read or learn additional information on that topic,” Broniarczyk said. “This miscalibrated sense of knowledge can be hard to correct.”
With IANS Inputs….