Collaboration focuses on improving knowledge regarding influence of social networks and individuals on dietary customs, microeconomic attitudes, and brand loyalty
ROI Checker, an artificial intelligence platform owned by Smart Data Track, LLC, a private company located in Northern Virginia, and the Human Nature Lab at Yale University announced today the beginning of a collaborative research project. The project is designed to improve and advance the knowledge of social networks formation and their influence on the individuals participating in them, in applied settings.
“We are pleased to enter into this agreement with the Human Nature Lab,” Lucas E. Wall, CEO and Founder of ROI Checker said. He added: “We value scientific progress and are very excited to be able to help to evaluate new hypotheses in the social networks field with the contribution of part of our big-data repositories. The outcome of this collaboration will advance not only Dr. Nicholas Christakis’ work on social influence and social contagion but also our effort to train artificial intelligence to explain and predict those two effects, among others. We believe these subjects have the ability to advance the general well-being of our society and look forward to sharing the results publicly.”
The collaboration is consistent with the Human Nature Lab work, which takes an interdisciplinary approach to understanding human social behavior. The laboratory integrates biological and social approaches to human nature, in what it is called biosocial science.
“We are excited to start this collaboration with the ROI Checker Artificial Intelligence Platform,” said Christakis, the Director of the lab. “People are interconnected, and so is their health and well-being. This collaboration with ROI Checker allows us to study how human tastes for food spread through social networks, and whether social connection can change our eating practices, or make us more generous.”
As part of this agreement, ROI Checker contributes a unique dataset containing primary longitudinal behavioral observations regarding consumption, financial attitudes, dietary habits, and social network formations. This unusual dataset is made possible by ROI Checker because of its proven expertise in dealing with big data extraction, data cleaning, data preparation, data analysis as well as modern data science, machine learning, and artificial intelligence.
ROI Checker is an artificial intelligence platform launched by Smart Data Track, LLC, a data science private company located in northern Virginia. ROI Checker is configured to detect, explain, and predict how information is used by individuals to influence their offline social networks and how those social networks affect their individual members. ROI Checker uses artificial intelligence to solve problems arising from the complexity of quantifying peer effects over time and the intricate mechanisms occurring within the social networks to which they belong. The state of the art in human social networks has experienced considerable improvement in recent years due to the work of many renowned scientists in the area. ROI Checker collaborates with some of the most prominent figures in the field to expand the body of work and science and bring science-backed solutions to the marketplace. ROI Checker is a project led by Lucas E. Wall, CEO and Founder of Smart Data Track, LLC. http://www.roichecker.com.
Smart Data Track, LLC, is a self-funded privately held company located in northern Virginia founded in 2012 to provide big data and data science advisory services. Smart Data Track, LLC was founded by Lucas E. Wall, who possesses more than fifteen years of professional experience in decision-making roles, including almost a decade of managing projects for Fortune 500 clients with the advisory arm of KPMG LLP, the accounting firm. Previously, Mr. Wall worked in Argentina during the severe recession and financial crisis spanning between 1998 and 2002. Smart Data Track, LLC supports clients with a portfolio of services aligned with the lifecycle of big data and data science. Smart Data Track, LLC, helps customers with efficient data extraction strategies, precise data analysis, preparation, and documentation, as well as development and implementation of artificial intelligence algorithms for a variety of purposes.
The Human Nature Lab is part of the Yale Institute for Network Science (YINS). The objective of the Yale Institute for Network Science (YINS) is to produce and disseminate knowledge related to network science, in all its forms and applications, and to make Yale a leader in the area. The Human Nature Lab takes an interdisciplinary – or transdisciplinary – approach to understanding human social behavior. It integrates biological and social approaches to human nature, in what they call biosocial science. The Human Nature Lab uses observational and experimental methods, including internet-based methods, to explore the ways in which biological and social factors conspire to influence human experience, over time intervals ranging from days to decades to eons. The Human Nature Lab is directed by Nicholas A. Christakis, MD, Ph.D., MPH.
Nicholas A. Christakis, MD, Ph.D., MPH, is a social scientist and physician who conducts research in the area of biosocial science, investigating the biological predicates and consequences of social phenomena. He directs the Human Nature Lab at Yale University, where he is appointed as the Sol Goldman Family Professor of Social and Natural Science, with appointments in the Departments of Sociology, Medicine, Ecology and Evolutionary Biology, and Biomedical Engineering. He is the Co-Director of the Yale Institute for Network Science. Dr. Christakis’ lab is currently focused on the structure and function of social networks. This research engages two types of phenomena: the social, mathematical, and biological rules governing how social networks form (“connection”), and the biological and social implications of how they operate to influence thoughts, feelings, and behaviors (“contagion”). Dr. Christakis’ research involves the application of network science methods and mathematical models to understand the dynamics of longitudinally evolving networks. To the extent that health behaviors such as smoking, drinking, or unhealthy eating spread within networks in clear ways, there are substantial implications for our understanding of health behavior and health policy. This body of work has also engaged the spread of obesity and emotional states such as happiness, depression, and loneliness. Another recent work has involved experiments examining the network spread of altruism. His book on the way social networks affect our lives, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives has been translated into nearly 20 foreign languages, and it has been widely reviewed. His main collaborator in this research is James Fowler. More recently, Dr. Christakis has become interested in the genetics and evolutionary biology of social network structure.