Researchers use machine learning to unearth underground Instagram "pods"

BROOKLYN, New York, Monday, April 27, 2020 – Likes, shares, followers, and comments are the currency of online social networks. Posts with high levels of engagement are prioritized by content curation algorithms, allowing social network "influencers" to monetize the size and loyalty of their audience. Yet not all engagement is organic, according to a team of researchers at New York University Tandon School of Engineering and Drexel University, who have published the first analysis of a robust underground ecosystem of "pods." These groups of users manipulate curation algorithms and artificially boost content popularity -- whether to increase the reach of promoted content or amplify rhetoric -- through a tactic known as "reciprocity abuse," whereby each member reciprocally interacts with content posted by other members of the group. The researchers also developed a machine learning tool to detect posts with a high likelihood of having gained popularity through pod engagement.