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Algorithm on social media may be discriminating

New York, April 22: A group of researchers have found that recommendation algorithms on social media platforms may discriminate on the basis of gender, age and race. According to researchers from Columbia University School of Engineering and Applied Science, social media and the sharing economy have created new opportunities by leveraging online networks to build trust and remove marketplace barriers. Their research suggested that old gender and racial biases persist — from men’s greater popularity on Twitter to African Americans’ lower acceptance rates on Airbnb. They used photo-sharing site Instagram as a test case and demonstrated how two common recommendation algorithms amplify a network effect known as homophily in which similar or like-minded people cluster together.
“We are simply showing how certain algorithms pick up patterns in the data. This becomes a problem when information spreading through the network is a job ad or other opportunity,” the study’s lead author Ana-Andreea Stoica said in a university statement. The team showed how algorithms turned loose on a network with homophily effectively make women less visible. They found that the women in their dataset — whose photos were slightly less likely to be ‘liked’ or commented on — became even less popular once recommendation algorithms were introduced. “Algorithms may put women at an even greater disadvantage,” Stoica added. (IANS)