By analyzing a rather large collection of words (a good fraction of a trillion) we extracted from the New York Times, music lyrics, the Google Books project, and Twitter, we’ve found that English is inherently positive. The manuscript is here, and some early press from Wired is here.
Within the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Previous findings are mixed: suggestive evidence of a positive bias has been found in small samples of English words [1-3], framed as the Pollyanna Hypothesis  and Linguistic Positivity Bias , while the experimental elicitation of emotional words has instead found a strong negative bias . Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is surprisingly invariant with respect to frequency of word use.