Like traditional broadcasters, social media platforms choose—through their algorithms—which stories to amplify and which to suppress. But unlike traditional broadcasters, the social media companies are not held accountable by any standards other than their own ever-changing decisions on the types of speech they will allow on their platforms.
And their algorithms are not transparent. Unlike on the evening news broadcast, no one can see what they have decided will be the top story of the day. No two people see exactly the same content in their personalized feeds. As a result, it is difficult for independent groups to track the spread of misinformation like the “Plandemic” video, which garnered millions of views on both Facebook and YouTube before being removed.
Source: The Markup
So we decided to try to monitor what is being algorithmically broadcast to social media users by bringing together a first-of-its-kind national panel of users who are paid to share their data to us. We started with Facebook, which has more than 2.7 billion monthly active users.
We built a custom standalone desktop application that was distributed to a panel of more than 1,000 paid participants. These panelists provided us with demographic information about themselves—gender, race, location, age, political leanings, and education level—and connected the Citizen Browser application to their personal Facebook accounts. The application periodically captures data from the panelists’ Facebook feeds.
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area.
He earned his MLIS degree from Wayne State University in Detroit.
Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.
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