Incorporating the Measurement of Moral Foundations Theory into Analyzing Stances on Controversial Topics
Complete page-faithful edition converted from the ACM version of record.
doi
10.1145/3465336.3475112
url
https://doi.org/10.1145/3465336.3475112
name
Incorporating the Measurement of Moral Foundations Theory into Analyzing Stances on Controversial Topics
pages
12
format
page-faithful facsimile
acm_url
https://dl.acm.org/doi/10.1145/3465336.3475112
authors
1.Rezvaneh Rezapour
2.Ly Dinh
3.Jana Diesner
doi_url
https://doi.org/10.1145/3465336.3475112
license
restricted
summary
Complete page-faithful edition converted from the ACM version of record.
abstract
This paper investigates the correlation between moral foundations and the expression of opinions in the form of stance on different issues of public interest. This work is based on the assumption that the formation of values (personal and societal) and language are interrelated, and that we can observe differences in points of view in user-generated text data. We leverage the Moral Foundations Theory to expand the scope of stance analysis by examining the narratives in favor or against several topics. Applying an expanded version of the Moral Foundations Dictionary to a benchmark dataset for stance analysis, we capture and analyze the relationships between moral values and polarized online discussions. Using this enhanced methodology, we find that each social issue has different “moral and lexical profiles.” While some social issues project more authority related words (Donald Trump), others consists of words related to care and purity (abortion and feminism). Our correlation analysis of stance and morality revealed notable associations between stances on social issues and various types of morality, such as care, fairness, and loyalty, hence demonstrating that there are certain morality types that are more attributed to stance classification than others. Overall, our analysis highlights the usefulness of considering morality when studying stance. The differences observed in various viewpoints and stances highlights linguistic variation in discourse, which may assist in analyzing cultural values and biases in society.
keywords
Moral Foundations Theory, stance analysis, social media, contro-
source_pdf
HT-2021_35-30_3465336/3465336.3475112.pdf
import_kind
full_text
open_access
false
publication
Proceedings of the 32nd ACM Conference on Hypertext and Social Media (HT ’21)
ccs_concepts
• Computing methodologies →Natural language processing;
displayAuthor
Rezvaneh Rezapour, Ly Dinh, Jana Diesner
source_sha256
ddca38abfdab579b0238ed092efc9a53ea1ebc8403d931f71140dfb47d897cde
publication_year
2021
source_attribution
Complete page images converted from the ACM version of record under supplied ACM publication authorization.