Happy words

Human languages tend to have more happy words than sad ones...
13 February 2015

Human languages are naturally dominated by words with positive associations, a new study has found.

A team of scientists selected 100,000 of the most used words in tenSmiley facelanguages from across the World and analysed whether they had inherently positive or negative meanings.

Words were harvested from a range of sources including books, newspapers, web pages, song lyrics and even Tweets in languages as diverse as English, Chinese, Russian, and Arabic. The top 10,000 words from each language were selected for analysis.

Native speakers rated each word on a happiness scale from 1 (strongly negative) to 9 (strongly positive). These scores were used to calculate the numbers of positive and negative words in each language.

Across all the languages studied there were more than twice as many positive as negative words. This wasn't simply due to the fact that people prefer saying nice things, because the positive bias was observed in both rare and common words.

"Language is our great social technology," explains Prof. Peter Dodds, a lead author on the paper. "I think it's encoding the fact that language is this glue that is connecting us together. Of course we must use it to talk about negative things, but for the most part we're discussing things that help us move along."

Although the trend was noticeable in all the languages studied there were some differences between languages, for example Brazilian Portuguese, Mexican Spanish and US English had the highest overall average happiness ratings, while Russian, Chinese and Korean were less so.

The researchers point out that this study focuses on each word in isolation, regardless of context. Their next step will be to use the analytical tools they've developed to expand the analysis to look at whole phrases, which will help give a more comprehensive picture of each language. Increasing the number of global languages analysed will also make the results more complete.

The hope is that this tool can be used to measure the public's feelings by analysing the words they're using. This information could be used to evaluate and make policy decisions.

"There are certain things you can measure well, and they get much more attention paid to them, and you can eventually make the mistake that they're the meaningful ones as well" continues Prof. Dodds.

"Our main hope has been to contribute another dial on the dashboard of society, next to the traditional ones like GDP... Everyone's wealth might be going up but if wellbeing is not going up then that's a problem... Instead of complaining about that, we're trying to get a number out there that people can focus on."

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