title: Data-Driven Engineering of Social Dynamics: Pattern Matching and Profit Maximization.
abstract: In this paper, we define a new problem related to social media, namely, the data-driven engineering of social dynamics. More precisely, given a set of observations from the past, we aim at finding the best short-term intervention that can lead to predefined long-term outcomes. Toward this end, we propose a general formulation that covers two useful engineering tasks as special cases, namely, pattern matching and profit maximization. By incorporating a deep learning model, we derive a solution using convex relaxation and quadratic-programming transformation. Moreover, we propose a data-driven evaluation method in place of the expensive field experiments. Using a Twitter dataset, we demonstrate the effectiveness of our dynamics engineering approach for both pattern matching and profit maximization, and study the multifaceted interplay among several important factors of dynamics engineering, such as solution validity, pattern-matching accuracy, and intervention cost. Finally, the method we propose is general enough to work with multi-dimensional time series, so it can potentially be used in many other applications.
authors.affiliation: Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Huan-Kai
authors.initials: HK
authors.lastname: Peng
authors.affiliation: Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Hao-Chih
authors.initials: HC
authors.lastname: Lee
authors.affiliation: Google Inc., Mountain View, California, United States of America.
authors.forename: Jia-Yu
authors.initials: JY
authors.lastname: Pan
authors.affiliation: Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Radu
authors.initials: R
authors.lastname: Marculescu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D061108:Social Media