Researchers from the University of Iowa (UI) have turned to social media to measure happiness.
UI's Chao Yang and colleagues mined Twitter for 3 billion tweets from October 2012 to October 2014, limiting their dataset to first-person tweets with the words "I," "me," or "mine" to increase the likelihood of getting messages that conveyed self-reflection. They worked with linguistics students to develop an algorithm that could capture the basic ways of expressing satisfaction or dissatisfaction with one's life.
The project was unique in that the researchers examined how users feel about their lives over time, instead of how they feel in the moment.
The researchers found people's feelings of long-term happiness and satisfaction with their lives remained steady over time, unaffected by external events such as elections, sports, or an earthquake in another country. Satisfied users were more active on Twitter longer, while dissatisfied users were more likely to use personal pronouns, conjunctions, and profanity in tweets.
The team would like to use the data to predict users who are at risk for changing from satisfied to dissatisfied.
From Iowa Now
View Full Article
Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA