title: Shaping Social Activity by Incentivizing Users.
abstract: Events in an online social network can be categorized roughly intoendogenousevents, where users just respond to the actions of their neighbors within the network, orexogenousevents, where users take actions due to drives external to the network. How much external drive should be provided to each user, such that the network activity can be steered towards a target state? In this paper, we model social events using multivariate Hawkes processes, which can capture both endogenous and exogenous event intensities, and derive a time dependent linear relation between the intensity of exogenous events and the overall network activity. Exploiting this connection, we develop a convex optimization framework for determining the required level of external drive in order for the network to reach a desired activity level. We experimented with event data gathered from Twitter, and show that our method can steer the activity of the network more accurately than alternatives.
authors.affiliation: Georgia Institute of Technology.
authors.forename: Mehrdad
authors.initials: M
authors.lastname: Farajtabar
authors.affiliation: Georgia Institute of Technology.
authors.forename: Nan
authors.initials: N
authors.lastname: Du
authors.affiliation: Max Plank Institute for Intelligent Systems.
authors.forename: Manuel Gomez
authors.initials: MG
authors.lastname: Rodriguez
authors.affiliation: University Carlos III in Madrid.
authors.forename: Isabel
authors.initials: I
authors.lastname: Valera
authors.affiliation: Georgia Institute of Technology.
authors.forename: Hongyuan
authors.initials: H
authors.lastname: Zha
authors.affiliation: Georgia Institute of Technology.
authors.forename: Le
authors.initials: L
authors.lastname: Song