Quantifying Latent Moral Foundations in Twitter Narratives: The Case of the Syrian White Helmets Misinformation

Ece Çiğdem Mutlu, Toktam Oghaz, Ege Tütüncüler, Jasser Jasser, Ivan Garibay

For years, many studies employed sentiment analysis to understand the reasoning behind people's choices and feelings, their communication styles, and the communities which they belong to. We argue that gaining more in-depth insight into moral dimensions coupled with sentiment analysis can potentially provide superior results. Understanding moral foundations can yield powerful results in terms of perceiving the intended meaning of the text data, as the concept of morality provides additional information on the unobservable characteristics of information processing and non-conscious cognitive processes. Therefore, we studied latent moral loadings of Syrian White Helmets-related tweets of Twitter users from April 1st, 2018 to April 30th, 2019. For the operationalization and quantification of moral rhetoric in tweets, we use Extended Moral Foundations Dictionary in which five psychological dimensions (Harm/Care, Fairness/Reciprocity, In-group/Loyalty, Authority/Respect and Purity/Sanctity) are considered. We show that people tend to share more tweets involving the virtue moral rhetoric than the tweets involving the vice rhetoric. We observe that the pattern of the moral rhetoric of tweets among these five dimensions are very similar during different time periods, while the strength of the five dimension is time-variant. Even though there is no significant difference between the use of Fairness/Reciprocity, In-group/Loyalty or Purity/Sanctity rhetoric, the less use of Harm/Care rhetoric is significant and remarkable. Besides, the strength of the moral rhetoric and the polarization in morality across people are mostly observed in tweets involving Harm/Care rhetoric despite the number of tweets involving the Harm/Care dimension is low.

Knowledge Graph

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