July 22, 2013 By News Staff
Is your community happy or unhappy? Some researchers say Twitter may have the answer.
A study released by a group of researchers from the University of Pennsylvania and Michigan State University states that language analysis used on Twitter can help determine a city’s overall well-being.
Why? "Tweeting is pervasive across the U.S.," according to the researchers. "And, unlike responses to surveys, tweets are not constrained to pre-chosen questions."
Using millions of tweets across the U.S. that had geo-location information, the researchers built a model of language that predicts well-being, and Twitter was an effective tool for significantly predicting such. In addition, the combination of Twitter language and socioeconomic information was more predictive than socioeconomic information on its own.
“What are tweets capturing about well-being?” the researchers wrote in a blog post about the report. “We didn’t want to just wind up with a happiness score, so the bulk of our work looked into this question by observing the actual words people use in regions with differing levels of life satisfaction.”
Words used on Twitter were grouped into a series of topics that more closely correlates to positive well-being as well as negative well-being.
The map developed from the study, pictured below, shows the life satisfaction of counties across the United States. Green regions have higher satisfaction, while red have lower.
All over the country, community leaders are looking to boost economic development through various initiatives. One key element in many of those initiatives is the use of information technology. When local governments build IT infrastructure, create e-government applications, assist high-tech startups or otherwise focus on technology, they create conditions that draw businesses to their communities and help retain skilled workers. This paper discusses and provides examples of these various ways local government can use technology to ultimately make a community more attractive to businesses, visitors and residents.