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Teaching computers to read is one thing. But by designing an algorithm that examined nearly 2 million posts from two popular parenting websites, a multidisciplinary team of UCLA researchers has built an elegant computational model that reflects how humans think and communicate, thereby teaching computers to understand structured narratives within the flow of posts on the internet.

The researchers said their success at managing large-scale data in this way highlights the overarching potential of machine learning, and demonstrates the capability to introduce counter-narratives into internet interactions, break up echo chambers and one day potentially help root out fact from fiction for social media users.

“Our question was, could we devise computational methods to discover an emerging narrative framework underlying internet conversations that was possibly influencing the decision making of many people throughout the country or possibly world?” said Timothy Tangherlini, lead author and a self-described “computational folklorist” who teaches folklore, literature and cultural studies in the Scandinavian section of the UCLA College.

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