Ding, TaoBickel, Warren K.Pan, Shimei2025-01-082025-01-082017-03-24https://doi.org/10.48550/arXiv.1703.07726http://hdl.handle.net/11603/37205Delay discounting, a behavioral measure of impulsivity, is often used to quantify the human tendency to choose a smaller, sooner reward (e.g., $1 today) over a larger, later reward ($2 tomorrow). Delay discounting and its relation to human decision making is a hot topic in economics and behavior science since pitting the demands of long-term goals against short term desires is among the most difficult tasks in human decision making [Hirsh et al., 2008]. Previously, small-scale studies based on questionnaires were used to analyze an individual’s delay discounting rate (DDR) and his/her realworld behavior (e.g., substance abuse) [Kirby et al., 1999]. In this research, we employ large-scale social media analytics to study DDR and its relation to people’s social media behavior (e.g., Facebook Likes). We also build computational models to automatically infer DDR from Social Media Likes. Our investigation has revealed interesting results.7 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Computer Science - Computers and SocietyComputer Science - Social and Information NetworksComputer Science - Artificial IntelligenceText