How Information Spreads
Information spreads fast on Facebook. We see that many social networks such as Facebook and Twitter have a resharing feature. The resharing or re-posting functionality allows users to share other people’s content with friends or followers. As social networkers, we re-share content from user to user. When we do, large cascades of reshares can form. Facebook scans and collects everything posted by each of your friends, everyone you follow, each group you belong to, and every Facebook page you’ve liked. It begs the question—why do some pieces of content go viral while others don’t? Why are some things shared more often than others? Lada Adamic will reveal how Facebook reshares cascades are formed, and she’ll discuss how they can be predicted based on things such as the content type, author, and diffusion structure.
About the Speaker
Lada Adamic is an American network scientist, who researches information dynamics in networks. She studies how network structure influences the flow of information, how information affects the evolution of networks and crowdsourced knowledge sharing.
Adamic is an associate professor at the University of Michigan. During her sabbatical year, she worked at Facebook with the data science team. Previously she worked in Hewlett-Packard‘s Information Dynamics Lab on research projects relating to networks constructed from large data sets.
About the Video: Information spreads fast on Facebook. We see that many social networks such as Facebook and Twitter have a resharing feature. The resharing or re-posting functionality allows users to share other people’s content with friends or followers. As social networkers, we re-share content from user to user.
About the speaker
Lada A. Adamic is a data scientist at Facebook (https://www.facebook.com/data) and an associate professor in the School of Information and the Center for the Study of Complex Systems at the University of Michigan. Her research interests center on information dynamics in networks: how information diffuses, how it can be found, and how it influences the evolution of a network's structure.