Collaborative Research: HNDS-R: Dynamics and Mechanisms of Information Spread via Social Media

There has never been so much information available at everyone's fingertips than there is today. Unfortunately, with so much information comes a lot of misinformation that can be spread to human populations and adopted by them as the truth. Understanding how information flows and its impact on human behavior is important for determining how to protect society from the effects of misinformation, propaganda, and "fake news." This project traces how information spreads on social media channels and how ideas, opinions, and beliefs change as they spread. Conducting this research requires combining concepts from computational social sciences, computer science, sociology, and statistics to understand the fundamentals of information spread in social media This project develops a new approach to the study of information diffusion that brings together several different mechanisms for information flow. Together these are used to analyze how information spreads in social media. The research has two main goals: First, it will spot and predict opinion trends and identify users' polarization on topics of broad interest to society (e.g., climate change or the Covid-19 pandemic). Second, it will track information propagation to understand its role in shaping opinion trends and identify the factors that are important for its spread and adoption. The researchers have access to a large amount of data that permits them to build and test large-scale models of information diffusion. The outcomes of this project include new computer algorithms that are capable of understanding information flow in social media and new avenues for research in the science of information spread and diffusion. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.