The New York Times & Science Feature UVM Happiness Research
- 10-10-2011
- By Dawn Marie Densmore

The New York Times and Science Magazine feature results from research on society’s well-being by Peter Sheridan Dodds and Christopher Danforth, professors in the Department of Mathematics and Statistics, Vermont Advanced Computing Center (VACC), and Complex Systems Center in the UVM College of Engineering and Mathematical Sciences (CEMS) in September 2011 issues. Dodds and Danforth’s research examined 4.6 billion tweets over nearly 3 years.
Their findings suggest that our moods are driven in part by a shared underlying biological rhythm that transcends culture and environment. By analyzing the frequency with which words occurred in their massive database of tweets, they saw patterns including happy weekends, and a morning peak in mood followed by an afternoon decline—“the daily unraveling of the human mind,” Dodds calls it. Other ‘happy” days often coincided with holidays, whereas especially unhappy days tended to coincide with unexpected events, such as the Japanese earthquake and tsunami. Their findings also hint at a global decline in mood starting in April 2009 that continues at least through the first half of 2011.
Peter Sheridan Dodds received a prestigious five-year $678,000 National Science Foundation (NSF) Faculty Early Career Development (CAREER) Award for his research entitled, "Explorations of Complex Social and Psychological Phenomena through Multiscale Online Sociological Experiments, Empirical Studies, and Theoretical Models." He is the twelfth UVM faculty member to receive a NSF Foundation CAREER Award given for research that equals the highest expectations of colleagues around the world.
To read the Science September 2011 Greg Miller article entitled, “Social Scientists Wade Into the Tweet Stream” visit: http://www.sciencemag.org/content/333/6051/1814.full
To read The New York Times article, “Twitter Study Tracks When We Are J” visit:
http://www.nytimes.com/2011/09/30/science/30twitter.html
For more on Twitter/Big Data:
http://www.sciencemag.org/site/multimedia/index.xhtml



