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In this week's episode of Social Science Weekly, we delve into the world of Twitter with a study that scrutinizes the functioning and implications of Twitter's ranking algorithm. The episode is based on the paper titled "Twitter’s Algorithm: Amplifying Anger, Animosity, and Affective Polarization", from researchers Smitha Millia, Micah Carroll, Sashrika Pandey, Yike Wang, and Anca D. Dragan from Cornell Tech and Berkeley Universities.

Looking at how Twitter's algorithm selects emotional content, its effects on preferences, and a surprising finding on the "echo chamber" phenomenon. We further break down the study's methodology, its limitations, and why its revelations matter to every Twitter user and those who value public discourse.

Whether you're a Twitter user curious about the unseen forces shaping your feed, or a social science enthusiast looking to understand the psychological and sociopolitical implications of algorithmic curation, this episode is sure to provide some food for thought.

Tune in to Social Science Weekly, to get just the facts, none of the spin, from the best and most important social science.