Robustness of emotion extraction from 20th century English books

In this paper, we test the robustness of emotion extraction from English language books published in the 20^th century. Our analysis is performed on a sample of the 8 million digitized books available in the Google Books Ngram corpus by applying three independent emotion detection tools: WordNet Affect, Linguistic Inquiry and Word Count, and a recently proposed `Hedonometer´ method. We also assess the statistical robustness of the extracted patterns as well as their outputs on specific parts of speech. The analysis confirms three main results: the existence of recognizable periods of positive and negative `literary affect´ from 1900 to 2000, a general decrease in the usage of emotion-related words in printed books that lasts at least until the 1980s, and, finally, a divergence between American and British books, with the former using more emotion-related words from the 1960s.