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dc.contributor.authorDodds, Peter S.
dc.date.accessioned2019-11-18T17:04:01Z
dc.date.available2019-11-18T17:04:01Z
dc.date.issued2019-11-06
dc.identifier.urihttp://hdl.handle.net/1853/62035
dc.descriptionPresented on November 6, 2019 at 3:00 p.m. in the Klaus Advanced Computing Building, Room 1116.en_US
dc.descriptionPeter S. Dodds is the Flint Professor of Mathematics and Statistics at the University of Vermont. His research focuses on system-level big data problems in many areas, including language and stories, sociotechnical systems, contagion, and ecology.en_US
dc.descriptionRuntime: 46:41 minutesen_US
dc.description.abstractI will survey our efforts at the Computational Story Lab to measure and study a wide array of social and cultural phenomena using “lexical meters” — online, interactive instruments that use social media and other texts to quantify population dynamics of human behavior. These include happiness, public health, obesity rates, and depression. I will explain how lexical meters work and how we have used them to uncover natural language encodings of positivity biases across cultures, universal emotional arcs of stories, links between social media posts and health, measures of fame and ultra-fame, and time compression for news. I will offer some thoughts on how fully developing a post-disciplinary, collaborative science of human stories is vital in our efforts to understand the evolution, stability, and fracturing of social systems.en_US
dc.format.extent46:41 minutes
dc.language.isoen_USen_US
dc.relation.ispartofseriesIDEaS Distinguished Lectureen_US
dc.subjectContagionen_US
dc.subjectFameen_US
dc.subjectStoriesen_US
dc.titleThe Science of Stories: Measuring and Exploring the Ecology of Human Stories with Lexical Instrumentsen_US
dc.typeLectureen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Institute for Data Engineering and Scienceen_US
dc.contributor.corporatenameUniversity of Vermont. Dept. of Mathematics and Statisticsen_US


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