top of page
TEXT: Content Attention and Engagement
Projects in the Text theme aim to develop a deeper understanding of how users engage with media content, what content factors may predict content success, and how to create content summaries.
We use controlled lab experiments and other social science methods, as well as machine learning, natural language processing, and statistical modeling to analyze human attention and interaction as it occurs in the real world.
Text Theme News
Text Theme Publications
Understanding Reader Backtracking Behavior in Online News Articles
Uzi Smajda, Max Grusky, Yoav Artzi, and Mor Naaman
Presented at WWW 2019.
bottom of page