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Sunday, August 9, 2020

The Extended Moral Foundations Dictionary (eMFD): Development and Applications

Hopp, F. R., Fisher, J. T., Cornell, D.,
Huskey, R., & Weber, R. (2020, June 12).


Moral intuitions are a central motivator in human behavior. Recent work highlights the importance of moral intuitions for understanding a wide range of issues ranging from online radicalization to vaccine hesitancy. Extracting and analyzing moral content in messages, narratives, and other forms of public discourse is a critical step toward understanding how the psychological influence of moral judgments unfolds at a global scale. Extant approaches for extracting moral content are limited in their ability to capture the intuitive nature of moral sensibilities, constraining their usefulness for understanding and predicting human moral behavior. Here we introduce the extended Moral Foundations Dictionary (eMFD), a dictionary-based tool for extracting moral content from textual corpora. The eMFD, unlike previous methods, is constructed from text annotations generated by a large sample of human coders. We demonstrate that the eMFD outperforms existing approaches in a variety of domains. We anticipate that the eMFD will contribute to advance the study of moral intuitions and their influence on social, psychological, and communicative processes.

From the Discussion:

In  a  series  of  theoretically-informed  dictionary  validation  procedures,  we  demonstrated  the  eMFD’s increased  utility  compared  to  previous  moral  dictionaries.  First,  we  showed  that  the  eMFD  more accurately  predicts  the  presence  of  morally-relevant  article  topics  compared  to  previous  dictionaries. Second, we showed that the eMFD more effectively detects distinctions between the moral language used by  partisan  news  organizations.  Word  scores  returned  by  the  eMFD  confirm  that  conservative  sources place greater emphasis on the binding moral foundations of loyalty, authority, and sanctity, whereas more liberal  leaning  sources  tend  to  stress  the  individualizing  foundations  of  care  and  fairness,  supporting previous research on moral partisan news framing (Fulgoni et al., 2016). Third, we demonstrated that the eMFD more accurately predicts the share counts of morally-loaded online newspaper articles. The eMFD produced  a  better  model  fit  explained  more  variance  in  overall  share  counts  compared  to  previous approaches.  Finally,  we  demonstrated eMFD score’s  utility  for  linking  moral  actions  to  their  respective moral agents and targets.