SoDa Symposium: “Socio-algorithmic Foundations of Trustworthy News Recommendation”
Event Start Date: Tuesday, February 27, 2024 - 12:30 pm
Event End Date: Tuesday, February 27, 2024 - 1:30 pm
Location: Virtual / Zoom EST
UMD students, faculty, staff, alumni, and friends—join us for the next SoDa Symposium!
Social media is now the main source of news for the majority of Americans and for billions of people worldwide. The recommendation algorithms employed by these platforms are designed to maximize views and clicks by finding engaging content, which in turn often ends up also amplifying stories from dubious news sources, conspiracy theories, and unverified rumors. This situation is especially concerning for partisan news consumers, who have a tendency to engage with information that conforms to their beliefs, regardless of its accuracy—ranking the news by (either predicted or achieved) popularity creates a self-sustaining cycle that prioritizes pro-attitudinal information regardless of its quality.
To break this loop, the project tests the hypothesis that prioritizing content that generates engagement in diverse audiences will improve the trustworthiness of recommendations. The objective of this research is to build a simulated social media platform that will allow researchers to test more robust news recommendation algorithms designed to improve the news consumption of social media users while recommending content that is still relevant to them. A key part of this endeavor is to design experiments combining survey-based collection of self-reported measures with observed behavioral outcomes of real-world social media behavior.
Ben Leff co-founded Verasight in 2020 with his former Cornell Government Professor, Peter K. Enns. Verasight’s mission is to expand access to high-quality survey data by building innovative methods to help organizations understand voters and consumers. Verasight’s clients include government agencies, academic researchers, Fortune 500 companies, and investors. Ben’s recent work has been featured in Bloomberg, Forbes, The Hill, and The Los Angeles Times. He began his career at Goldman Sachs and graduated from the Stanford Graduate School of Business as an Arjay Miller Scholar.
Giovanni Luca Ciampaglia is an assistant professor at the College of Information Studies at the University of Maryland. He holds a Laurea in Computer Science from the “Sapienza” University of Rome and a Ph.D. in Computer Science from the University of Lugano. He is interested in problems originating from the collective interplay between people and computing systems, such as information propagation on social media, knowledge production in online communities, and trustworthiness in cyberspace. His work has been covered in major news outlets, including the Wall Street Journal, Wired, NPR, and CBS News.
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Speaker(s): Ben Leff, Giovanni Luca Ciampaglia