Robustness of emotion extraction from 20th century English books

Alberto Acerbi*, Vasileios Lampos, R. Alexander Bentley

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

In this paper, we test the robustness of emotion extraction from English language books published in the 20th 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.

Original languageEnglish
Title of host publication2013 IEEE INTERNATIONAL CONFERENCE ON BIG DATA
Editors Hu, TY Lin, Raghavan, B Wah, R BaezaYates, G Fox, C Shahabi, M Smith, Q Yang, R Ghani, W Fan, R Lempel, R Nambiar
Place of PublicationNEW YORK
PublisherIEEE Computer Society
Number of pages8
ISBN (Print)978-1-4799-1293-3
Publication statusPublished - 2013
EventIEEE International Conference on Big Data (Big Data) - Santa Clara, Canada
Duration: 6 Oct 20139 Oct 2013

Conference

ConferenceIEEE International Conference on Big Data (Big Data)
CountryCanada
Period6/10/139/10/13

Keywords

  • EVOLUTION

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