Where: Luddy Center for Artificial Intelligence (LU2005)
Speaker: Ankur Mani
Title: Investigating Churn in Online Wellness Programs: Evidence from a U.S. Online Social Network
Online wellness activity platforms increasingly utilize wellness programs and social support to motivate healthy activities and improve user engagement. However, many wellness programs suffer from high churn rates that discount their expected efficacy, and negative social influence may lead to a churn contagion that amplifies the churn speed and scale. Hence, a need arises to understand why users churn wellness programs and how social contagion contributes to the churns. Leveraging the exercise challenge setting, the exercise data, and a large social network on a renowned U.S. online fitness platform, we investigate the effect of peers’ behavior in exercise challenge churn on ego. To achieve the research goal, we employ an instrumental variable framework (shown in the figure below), using the exogenous variation of peers’ weather in locations that differ from the ego’s location as instruments. The framework untangles the endogeneity of the estimated effect using variations created by peers’ weather as a shock to the ego’s churn. We measure churn as a decision an ego makes after being inactive for one to two weeks and define peers as the ones an ego follows on the platform. We find that exercise challenge churn is socially contagious and demonstrates a complex contagion. Interestingly, our analyses reveal that the social contagion of churn diffuses from the sub-central or peripheral egos with fewer friends in the social network to central egos with more friends in the social network. Such churn contagion is mostly confined to low-density network communities with members who are poorly connected. Our findings have important implications for designing intervention plans to stop online wellness program churn based on social contagion.
This is joint work with my student Yi Zhu.
Ankur Mani is an assistant professor in the Industrial and Systems Engineering department at the University of Minnesota. He is also an affiliate of the Data Science Initiative and Control Systems and Dynamics Group at the University of Minnesota. He received his Ph.D. from the Massachusetts Institute of Technology and B.Tech. degree from the Indian Institute of Technology, Delhi. Ankur’s research interests include networks, distributed experimentation, and game theory with applications in social networks, supply chain networks, transportation networks and health care. His research has been published in major journals including Management Science and Nature Human Behavior among others and has received recognitions from the INFORMS revenue management section, INFORMS aviation section, and POMS, among others.
Santo Fortunato has been elected Fellow of the American Physical Society (APS)for foundational contributions to the statistical physics of complex networks, and particularly to the study of community detection in networks and applications to social and scientific networks. The Fellowship is awarded annually to no more than one half of one percent of members of the APS for exceptional contributions to physics through research or publications, important applications of physics, leadership and physics education. Check the official press release of the school!
Santo Fortunato has been elected Fellow of the Network Science Society (NSS) for seminal work in network community structure leading to advances in multiresolution approaches and validation, and for contributions to disseminating network science. The Fellowship is awarded annually to members of the community for their exceptional lifelong individual contributions to any area of network science research and to the community of network scientists, both locally and globally. The award has been announced at NetSci 2022, the flagship event of the NSS. Fortunato is the first member of Luddy to receive this prestigious recognition. Check the official press release of the school!
The Army Research Office has awarded the grant Multilayer network embeddings and applications to real-world problems to CNetS faculty Santo Fortunato and Filippo Radicchi. The project lies at the interface between artificial intelligence and network science and aims at developing embeddings of multilayer networks in vector space. While graph embeddings have become very popular over the past decade, most of the research in this area focuses on the analysis of isolated graphs. However, networks in the real world do not exist in isolation, but they are coupled with other networks. For example in social media, the same person may interact with different individuals depending on the online platform.
The Indiana University Network Science Institute (IUNI), jointly with the Network Science Institute at Northeastern University (NetSI) are organizing SINSA 2020, the first Summer Institute in Network Science and its Applications, a two-weeks long school divided into eight teaching modules on major topics of network science, with top instructors, intended for graduate students, practitioners and early-career researchers. Santo Fortunato, CNetS member and IUNI Director, is one of the two chairs of this event, as well as instructor of the module Network Structures. SINSA 2020 will be held in Boston, from June 22 till July 3, 2020. Send your students to this great event!
The outcome of the DREAM Challenge on Disease Module Identification in genetic networks has been reported in a paper published in Nature Methods. Over 400 participants from all around the world have contributed 75 different clustering algorithms to predict disease-relevant modules in diverse gene and protein networks. Participants could only use unsupervised clustering algorithms, which rely exclusively on the network structure and do not depend on additional biological information such as known disease genes. CNetS professor Santo Fortunato and former postdoc Lucas Jeub participated in the analysis of the results delivered by the algorithms.