Researcher proposes a system to analyse credibility of tweets

A team led by Georgia Tech PhD candidate Tanushree Mitra scanned 66 million tweets linked to nearly 1,400 real-world events to build a language model that identified words and phrases that lead to strong or weak perceived levels of credibility on Twitter. 

“Tweets with booster words, such as ‘undeniable,’ and positive emotion terms, such as ‘eager’ and ‘terrific,’ were viewed as highly credible,” Mitra said.  

The team looked at tweets surrounding events in 2014 and 2015, including the emergence of Ebola in West Africa, the Charlie Hebdo attack in Paris and the death of Eric Garner in New York City.