At BuzzFeed we generate hundreds of articles a day, so choosing better headlines can save us from substantial losses in our audience engagement. Our solution is a tool that takes in multiple headline and thumbnail options for an article and decides which combination is most effective. In this talk, I discuss the models that perform best for this tool under different product scenarios. I also discuss causal analysis of the effectiveness of this tool when A/B testing is infeasible.
Lucy X Wang is a Senior Data Scientist at BuzzFeed working on machine learning tools for optimizing audience reach and engagement. She holds an MS in Computer Science from Columbia University where she performed research on social networks and information diffusion.