Spend enough time on the internet, and you might start feeling an inescapable sense of melancholy from the constant barrage of bad news, mean-spirited tweets, and divisive Facebook posts from that guy you haven’t spoken to since high school. But while an endless stream of depressing words scrolling across your laptop screen might put you in a funk, a new study indicates that language itself isn’t necessarily such a bummer; There may, in fact, be an inherent trend toward the positive across the spectrum of human languages.
For their study “Human Language Reveals a Universal Positivity Bias,” published this week in the Proceedings of the National Academy of the Sciences, a team of mathematicians from the University Of Vermont lead by Peter Dodds looked across ten different languages including English, Arabic, and simplified Chinese, compiling thousands of the most used words culled from literature, social media, even song lyrics. Using native speakers to asses the various compiled words in terms of their positivity, the team concluding there is:
…evidence of a deep imprint of human sociality in language, [and] that (i) the words of natural human language possess a universal positivity bias, (ii) the estimated emotional content of words is consistent between languages under translation, and (iii) this positivity bias is strongly independent of frequency of word use.
For those who insist on keeping score, Spanish reportedly has the strongest bias toward positivity, while Chinese rankes last. Still, the overall trend, the researchers found, indicated a positivity bias across all languages.
As the paper notes, this is effectively a data-driven confirmation of—or at least supporting evidence for—what’s known as the “Pollyanna Hypothesis,” a 1969 theory by University of Illinois researchers Jerry Boucher and Charles Osgood, which theorizes “a universal human tendency to use evaluatively positive words more frequently and diversely than evaluatively negative words.” As Vice’s Motherboard points out, these types of evaluative language studies have been around for a while, with Dodds himself having done a similar – if more limited – one in 2012. But while that project, and Boucher/Osgood’s 1969 work, focused specifically on English, Dodds latest research, he explained to Motherboard represents a “leap forward in terms of the scope of data-based approaches to language analysis.”
While the study seems to confirm a language bias toward positivity, it’s not without limitations. Factors such as word-context were not taken into account, nor does the study ultimately answer whether language makes humans naturally happy, or if humans are happy, and the observed positivity is byproduct thereof. Rather, Dodds told Motherboard, this study is simply a starting place for scientists to conduct more complex, more comprehensive language analysis.
Given that ninety percent of the world’s six thousand or so languages are may be set to go extinct in the next hundred years, they’d better hurry.
