Nobel laureate Robert Shiller is one of few economists to have predicted both the Great Recession of 2007–2009 and the dot-com crash. Throughout his career, Shiller has introduced and supported groundbreaking ideas in economics, and in 2017, he presented “”https://cowles.yale.edu/sites/default/files/files/pub/d20/d2069.pdf">Narrative Economics" at the National Bureau of Economic Research (NBER). The paper introduced two key concepts:
The term “narratives” refers to stories or ideas, particularly those of human interest and emotion that are conveyed in communication. The human brain has always been highly attuned to narratives, whether factual or not, to justify ongoing actions. Stories motivate and connect activities to deeply felt values and needs. When narratives “go viral,” they spread far and wide and are often accompanied by deep sociopolitical and economic change. The 1920–21 Depression, the Great Depression of the 1930s, the Great Recession of 2007–9, and today’s contentious political-economic situation are all considered the results of the popular narratives of their respective times.
The interpretation of narratives is a subjective human phenomenon and is difficult to study scientifically. Narrative extraction is the first step to this end. Narrative extraction is particularly relevant today, when “fake news” and the manipulation of social media propagate stories that have motivated human action, for example, during the 2016 US election or the Brexit referendum. Beyond these not-so-trivial matters, research in this area will assist corporations in understanding brand value dynamics and the virality of products and will enable improved modeling of a product’s diffusion of innovation curve. Spreading narratives have been creating cultural change long before the internet or the advent of social media. However, the dynamics of this phenomena have both accelerated and become more decentralized. Narratives traverse the “Dunbar’s number” threshold far more frequently than ever before and appear to influence a greater multiplicity of social groups.
Naveed Ghaffar and Rashed Iqbal outline a framework that uses natural language understanding to extract and analyze narratives in human communication in order to help us gain a better understanding of how “viral” narratives emerge as well as their likely impact. The approach involves:
Naveed Ghaffar is the cofounder of Narrative Economics, a startup that is leading research and development in the emerging field of natural language understanding as it pertains to the spread of popular narratives across the world. A serial entrepreneur and innovator in data management and data science technologies, Naveed has founded three startups in this domain over the past six years and continues to coach and mentor a number of London-based startups. Most recently, Naveed was chief engineer for KPMG McLaren, where he was responsible for overall product management for the company’s suite of data analytics and simulation solutions. Naveed’s background is in data analytics and data governance. He is recognized as a thought leader on privacy by design, design thinking, and the policy and technical effects of the EU GDPR regulations. Naveed holds a degree in law (LLB honors) and an MSc from the University of Birmingham. He is a Certified Scrum Master, design thinking coach, and jobs-to-be-done innovator.
Rashed Iqbal is a program manager for data solutions at Teledyne Technologies in California as well as an adjunct professor in the Economics Department at UCLA, where he teaches graduate courses in data science. Rashed also teaches a course on deep learning and natural language processing and understanding at UC Irvine. His current area of research is narrative economics, which studies the impact of popular narratives and stories on economic fluctuations. He believes narrative extraction will revolutionize process of human communication. His other areas of interest and expertise include data science, machine learning, and transitioning traditional organizations to Agile and Lean methods. Rashed has led multiple entrepreneurial ventures in these areas. He holds a PhD in systems engineering with a focus on stochastic and predictive systems as well as current CSM, CSP, PMI-ACP, and PMP certifications. He is a senior member of the IEEE.
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