According to a new study carried out by a group of scientists including Dr Peter Dodds from the University of Vermont, all human languages skew toward the use of happy words.
This graph shows distributions of perceived average word happiness from 24 sources in ten languages. Spanish is most skewed toward the positive and Chinese books the least – but all sources showed the same trend: humans tend to look on, and talk about, the bright side of life; the yellow and blue graphs, called histograms, each represent the 5,000 most commonly used words from each source; yellow indicates positivity; blue indicates negativity. Image credit: Peter Sheridan Dodds et al.
In 1969, Dr Jerry Boucher and Dr Charles E. Osgood of the University of Illinois proposed what they called the Pollyanna Hypothesis – the idea that there is a universal human tendency to use evaluatively positive words.
Now, Dr Dodds and his colleagues have applied a Big Data approach – using a massive data set of many billions of words, based on actual usage, rather than expert opinion – to test the hypothesis.
“We looked at ten languages. And in every source we looked at, people use more positive words than negative ones,” said Dr Dodds, who is the first author of a paper published in the Proceedings of the National Academy of Sciences.
“But doesn’t our global torrent of cursing on Twitter, horror movies, and endless media stories on the disaster du jour mean this can’t be true? No. This huge study of the atoms of language – individual words – indicates that language itself has a positive outlook,” he said.
“And, therefore, it seems that positive social interaction is built into its fundamental structure.”
To deeply explore the Pollyanna Hypothesis, the scientists gathered billions of words from around the world using 24 types of sources including books, news outlets, social media, websites, television and movie subtitles, and music lyrics.
For example, they collected roughly one hundred billion words written in tweets.
From these sources, they then identified about 10,000 of the most frequently used words in each of ten languages including English, Spanish, French, German, Brazilian Portuguese, Korean, Chinese (simplified), Russian, Indonesian and Arabic.
Next, they paid native speakers to rate all these frequently-used words on a 9-point scale from a deeply frowning face to a broadly smiling one.
From these native speakers, they gathered 5 million individual human scores of the words.
Averaging these, in English for example, ‘laughter’ rated 8.50, ‘food’ 7.44, ‘truck’ 5.48, ‘the’ 4.98.
A Google web crawl of Spanish-language sites had the highest average word happiness, and a search of Chinese books had the lowest, but – and here’s the point – all twenty-four sources of words that they analyzed skewed above the neutral score of five on their one-to-nine scale – regardless of the language.
In every language, neutral words like “the” scored just where you would expect: in the middle, near five.
And when the team translated words between languages and then back again they found that the estimated emotional content of words is consistent between languages.
In all cases, the scientists found a usage-invariant positivity bias.
In other words, they found that, on average, people use more happy words than sad words.
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Peter Sheridan Dodds et al. Human language reveals a universal positivity bias. PNAS, published online February 09, 2015; doi: 10.1073/pnas.1411678112
