@conference {1500623,
	title = {Influence Maximization in the Field: The Arduous Journey from Emerging to Deployed Application},
	booktitle = {International Conference on Autonomous Agents and Multi-agent Systems (AAMAS)},
	year = {2017},
	abstract = {This paper focuses on a topic that is insufficiently addressed in the literature, i.e., challenges faced in transitioning agents from an emerging phase in the lab, to a deployed application in the field. Specifically, we focus on challenges faced in transitioning HEALER and DOSIM, two agents for social influence maximization, which assist service providers in maximizing HIV awareness in real-world homeless-youth social networks. These agents recommend key "seed" nodes in social networks, i.e., homeless youth who would maximize HIV awareness in their real-world social network. While prior research on these agents published promising simulation results from the lab, this paper illustrates that transitioning these agents from the lab into the real-world is not straightforward, and outlines three major lessons. First, it is important to conduct real-world pilot tests; indeed, due to the health-critical nature of the domain and complex influence spread models used by these agents, it is important to conduct field tests to ensure the real-world usability and effectiveness of these agents. We present results from three real-world pilot studies, involving 173 homeless youth in an American city. These are the first such pilot studies which provide headto-head comparison of different agents for social influence maximization, including a comparison with a baseline approach. Second, we present analyses of these real-world results, illustrating the strengths and weaknesses of different influence maximization approaches we compare. Third, we present research and deployment challenges revealed in conducting these pilot tests, and propose solutions to address them. These challenges and proposed solutions are instructive in assisting the transition of agents focused on social influence maximization from the emerging to the deployed application phase.},
	author = {Amulya Yadav and Bryan Wilder and Eric Rice and Petering, Robin and Craddock, Jaih and Yoshioka-Maxwell, Amanda and Hemler, Mary and Onasch-Vera, Laura and Tambe, Milind and Woo, Darlene}
}
