Extracting Latent Moral Information from Text Narratives: Relevance, Challenges, and Solutions

René Weber, J. Michael Mangus, Richard Huskey, Frederic R. Hopp, Ori Amir, Reid Swanson, Andrew Gordon, Peter Khooshabeh, Lindsay Hahn, Ron Tamborini

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


Moral Foundations Theory (MFT) and the Model of Intuitive Morality and Exemplars (MIME) contend that moral judgments are built on a universal set of basic moral intuitions. A large body of research has supported many of MFT’s and the MIME’s central hypotheses. Yet, an important prerequisite of this research—the ability to extract latent moral content represented in media stimuli with a reliable procedure—has not been systematically studied. In this article, we subject different extraction procedures to rigorous tests, underscore challenges by identifying a range of reliabilities, develop new reliability test and coding procedures employing computational methods, and provide solutions that maximize the reliability and validity of moral intuition extraction. In six content analytical studies, including a large crowd-based study, we demonstrate that: (1) traditional content analytical approaches lead to rather low reliabilities; (2) variation in coding reliabilities can be predicted by both text features and characteristics of the human coders; and (3) reliability is largely unaffected by the detail of coder training. We show that a coding task with simplified training and a coding technique that treats moral foundations as fast, spontaneous intuitions leads to acceptable inter-rater agreement, and potentially to more valid moral intuition extractions. While this study was motivated by issues related to MFT and MIME research, the methods and findings in this study have implications for extracting latent content from text narratives that go beyond moral information. Accordingly, we provide a tool for researchers interested in applying this new approach in their own work.

Original languageEnglish
Pages (from-to)119-139
Number of pages21
JournalCommunication Methods and Measures
Issue number2-3
StatePublished - 3 Apr 2018

Bibliographical note

Publisher Copyright:
© 2018 Taylor & Francis Group, LLC.


Dive into the research topics of 'Extracting Latent Moral Information from Text Narratives: Relevance, Challenges, and Solutions'. Together they form a unique fingerprint.

Cite this