Is it all downhill from here? Researchers at the Columbia University have found that algorithms of various existing social media platforms take a rather sexist approach when it comes to dealing with women's profiles.
Apparently, algorithms have been found to be discriminating against women by making them less visible, thus causing a reduction in their popularity. For instance, it was found that men have greater popularity on Twitter.
Besides that, researchers also believe that racial biases persist as well, with African Americans having lower acceptance on platforms like Airbnb.
The Columbia University researchers used Instagram as a test case, which showed how two common recommendation algorithm amplify a network effect known as homophily in which similar or like-minded people cluster together. The research further found that social media platforms with homophily basically make women less discoverable. And to top that, women in the dataset, who have photos that are less likely to be “liked” by other users on the platform, are further pushed down on the visibility scale.
"We are simply showing how certain algorithms pick up patterns in the data," Ana-Andreea Stoica, a graduate student at the university, said. "This becomes a problem when information spreading through the network is a job ad or other opportunity. Algorithms may put women at an even greater disadvantage," she added.
The data was scraped by these university researchers from Instagram in 2014, after Facebook bought the company but before automated prompts for friend recommendations came up.
Despite women occupying the larger chunk of the sample of 550,000 Instagram users, the researchers found that photos shared by men tended to be better received. Apparently, 52 percent of men received at least 10 likes or comments compared to 48 percent of women.
Researchers also found that the disparity was greatest among Instagram's super-influencers. When algorithms were turned loose on this particular network of ultra-engaging individuals, women's visibility plunged.
Even though women in the top 0.1 percent for engagement outnumbered men, it was found that men were still more likely to be suggested to new users.