Social media such as Twitter and Facebook provide a rich, if imperfect, portal into people's lives. We analyse tens of millions of Facebook posts and billions of tweets to study variation in language use with age, gender, personality, and mental and physical well-being. Word clouds provide insights into stress, anxiety, and depression, while correlations between language use and county-level health data suggest connections between health and happiness, including potential psychological causes of heart disease.
*C4E 101: Series of Lectures in Innovation and Entrepreneurship APPROVED
Dr. Lyle Ungar Professor of Computer and Information Science at the University of Pennsylvania
Dr. Lyle Ungar is a Professor of Computer and Information Science at the University of Pennsylvania, where he also holds appointments in multiple departments in the Schools of Business (Wharton), Medicine, Arts and Sciences, and Engineering and Applied Science. Lyle received a B.S. from Stanford University and a Ph.D. from M.I.T. He has published over 250 articles, supervised two dozen PhD students, and is co-inventor on ten patents. His current research focuses on developing scalable machine learning methods for data mining and text mining, including deep learning methods for natural language processing, and analysis of social media to better understand the drivers of physical and mental well-being.
Tuesday March 12th 16:00
Learning Resource Centre "Stelios Ioannou", Room 012 University of Cyprus
Centre of Entrepreneurship
MBA Program of the University of Cyprus