Movie subtitles in Arabic, Twitter feeds in Korean, the famously dark literature of Russia, websites in Chinese, music lyrics in English, and even the war-torn pages of the New York Times -- the researchers found that these, and probably all human languages, skew toward the use of happy words.
"We looked at 10 languages and in every source we looked at, people use more positive words than negative ones," said mathematician Peter Dodds who co-led the study.
In 1969, two psychologists at the University of Illinois proposed what they called the Pollyanna Hypothesis - the idea that there is a universal human tendency to use positive words more frequently than negative ones.
"Put even more simply," they wrote, "humans tend to look on (and talk about) the bright side of life."
It was a speculation that has provoked debate ever since.
For the new study, the team of scientists with support from the US National Science Foundation and the non-profit Mitre Corporation gathered billions of words from around the world using 24 types of sources.
The sources were books, news outlets, social media, websites, television and movie subtitles, and music lyrics.
In all cases, the scientists found "a usage-invariant positivity bias", as they wrote in the study.
In other words, by looking at the words people actually use most often they found that, on an average, we "use more happy words than sad words", added mathematician Chris Danforth who co-led the new research.
The team has developed "physical-like instruments" for both real-time and offline measurements of the happiness in large-scale texts -- "basically, huge bags of words", Danforth said.
They called this instrument a "hedonometer" - a happiness meter.
It can now trace the global happiness signal from English-language Twitter posts on a near-real-time basis, and show differing happiness signals between days.
The study appeared in the journal Proceedings of the National Academy of Sciences.