@article{ref1,
title="Avoid violence, rioting, and outrage; approach celebration, delight, and strength: using large text corpora to compute valence, arousal, and the basic emotions",
journal="Quarterly journal of experimental psychology (2006)",
year="2015",
author="Westbury, Chris and Keith, Jeff and Briesemeister, Benny B. and Hofmann, Markus J. and Jacobs, Arthur M.",
volume="68",
number="8",
pages="1599-1622",
abstract="Ever since Aristotle discussed the issue in Book II of his Rhetoric, humans have attempted to identify a set of &quot;basic emotion labels&quot;. In this paper we propose an algorithmic method for evaluating sets of basic emotion labels that relies upon computed co-occurrence distances between words in a 12.7-billion-word corpus of unselected text from USENET discussion groups. Our method uses the relationship between human arousal and valence ratings collected for a large list of words, and the co-occurrence similarity between each word and emotion labels. We assess how well the words in each of 12 emotion label sets-proposed by various researchers over the past 118 years-predict the arousal and valence ratings on a test and validation dataset, each consisting of over 5970 items. We also assess how well these emotion labels predict lexical decision residuals (LDRTs), after co-varying out the effects attributable to basic lexical predictors. We then demonstrate a generalization of our method to determine the most predictive &quot;basic&quot; emotion labels from among all of the putative models of basic emotion that we considered. As well as contributing empirical data towards the development of a more rigorous definition of basic emotions, our method makes it possible to derive principled computational estimates of emotionality-specifically, of arousal and valence-for all words in the language.<p /> <p>Language: en</p>",
language="en",
issn="1747-0218",
doi="10.1080/17470218.2014.970204",
url="http://dx.doi.org/10.1080/17470218.2014.970204"
}