Related papers: Engagement Maximization
We propose information-directed sampling -- a new approach to online optimization problems in which a decision-maker must balance between exploration and exploitation while learning from partial feedback. Each action is sampled in a manner…
The engagement of each user in a social network is an essential indicator for maintaining a sustainable service. Existing studies use the $coreness$ of a user to well estimate its static engagement in a network. However, when the engagement…
How can a system designer exploit system-level knowledge to derive incentives to optimally influence social behavior? The literature on network routing contains many results studying the application of monetary tolls to influence behavior…
From media platforms to chatbots, algorithms shape how people interact, learn, and discover information. Such interactions between users and an algorithm often unfold over multiple steps, during which strategic users can guide the algorithm…
In digital markets comprised of many competing services, each user chooses between multiple service providers according to their preferences, and the chosen service makes use of the user data to incrementally improve its model. The service…
We consider a multi-user network where a network manager and selfish users interact. The network manager monitors the behavior of users and intervenes in the interaction among users if necessary, while users make decisions independently to…
In random-access communication systems, the number of active users varies with time, and has considerable bearing on receiver's performance. Thus, techniques aimed at identifying not only the information transmitted, but also that number,…
Open-domain dialog systems have a user-centric goal: to provide humans with an engaging conversation experience. User engagement is one of the most important metrics for evaluating open-domain dialog systems, and could also be used as…
In the digital environment, human attention is frequently guided by cognitive heuristics rather than deliberate evaluation. Since low-credibility narratives often lack substantive factual evidence, their diffusion disproportionally relies…
We study a Bayesian persuasion problem with externalities. In this model, a principal sends signals to inform multiple agents about the state of the world. Simultaneously, due to the existence of externalities in the agents' utilities, the…
Social-media platforms are one of the most prevalent communication media today. In such systems, a large amount of content is generated and available to the platform. However, not all content can be transmitted to every possible user at all…
Modern computational systems have an unprecedented ability to detect, leverage and influence human attention. Prior work identified user engagement and dwell time as two key metrics of attention in digital environments, but these metrics…
Numerous online services are data-driven: the behavior of users affects the system's parameters, and the system's parameters affect the users' experience of the service, which in turn affects the way users may interact with the system. For…
This paper describes a novel approach to systematically improve information interactions based solely on its wording. Following an interdisciplinary literature review, we recognized three key attributes of words that drive user engagement:…
A monopolist seller of multiple goods screens a buyer whose type is initially unknown to both but drawn from a commonly known distribution. The buyer privately learns about his type via a signal. We derive the seller's optimal mechanism in…
This study explores the relationship between textual features and Information Engagement (IE) on digital platforms. It highlights the impact of computational linguistics and analytics on user interaction. The READ model is introduced to…
Imitation learning uses data for training policies to solve complex tasks. However, when the training data is collected from human demonstrators, it often leads to multimodal distributions because of the variability in human actions. Most…
We study a dynamic model of Bayesian persuasion in sequential decision-making settings. An informed principal observes an external parameter of the world and advises an uninformed agent about actions to take over time. The agent takes…
Large quantities of data flow on the internet. When a user decides to help the spread of a piece of information (by retweeting, liking, posting content), most research works assumes she does so according to information's content,…
As the rate of content production grows, we must make a staggering number of daily decisions about what information is worth acting on. For any flourishing online social media system, users can barely keep up with the new content shared by…