TY - GEN
T1 - Influence maximization in the field
T2 - 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
AU - Yadav, Amulya
AU - Wilder, Bryan
AU - Rice, Eric
AU - Petering, Robin
AU - Craddock, Jaih
AU - Yoshioka-Maxwell, Amanda
AU - Hemler, Mary
AU - Onasch-Vera, Laura
AU - Tambe, Milind
AU - Woo, Darlene
N1 - Publisher Copyright:
© Copyright 2017, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All Rights Reserved.
PY - 2017
Y1 - 2017
N2 - 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 DOSLM, 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 head-To-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.
AB - 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 DOSLM, 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 head-To-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.
UR - http://www.scopus.com/inward/record.url?scp=85038624768&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85038624768&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85038624768
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 150
EP - 158
BT - 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
A2 - Durfee, Edmund
A2 - Das, Sanmay
A2 - Larson, Kate
A2 - Winikoff, Michael
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Y2 - 8 May 2017 through 12 May 2017
ER -