Challenge: Recent studies have focused on detecting moral values in political communication, trying to identify moral frames used by political actors or parties to convey their messages.
Approach: They propose to code German parliamentary debates to identify moral framing and to detect subtle differences in politicians’ moral framming.
Outcome: The proposed model distinguishes between different types of moral frames and includes narrative roles, together with the moral foundations for each frame.

Similar Papers

Classification of Moral Foundations in Microblog Political Discourse (P18-1)

Copied to clipboard

Challenge: a recent study shows correlation between political ideologies and moral foundations expressed in text . a moral foundation theory suggests that there are five basic moral values which underlie human moral perspectives .
Approach: They propose to model the moral foundations of tweets by using an annotation framework . they propose to use policy frames to predict the morality of political tweets .
Outcome: The proposed model can predict moral foundations of political tweets, the authors show . their model can be used to predict political slogans and political ideologies, they say .
Identifying Morality Frames in Political Tweets using Relational Learning (2021.emnlp-main)

Copied to clipboard

Challenge: Moral sentiment is often motivated by its targets, which can correspond to individuals or collective entities.
Approach: They propose a model to predict moral attitudes towards entities and moral foundations jointly using tweets written by US politicians.
Outcome: The proposed model predicts moral attitudes towards entities and moral foundations jointly from tweets written by US politicians.
Moral Foundations of Large Language Models (2024.emnlp-main)

Copied to clipboard

Challenge: Moral foundations theory (MFT) is a psychological assessment tool that decomposes human moral reasoning into five factors, including care/harm, liberty/oppression, and sanctity/degradation.
Approach: They propose to use moral foundations theory to analyze whether popular LLMs have acquired a bias towards a particular set of moral values.
Outcome: The proposed model can be adversarially selected to exhibit a particular moral foundations and can affect downstream tasks.
The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments (2022.acl-long)

Copied to clipboard

Challenge: Existing arguments that focus on shared values are based on prior beliefs and morals, but little research has been done on the effectiveness of these proxies.
Approach: They propose a system that automatically generates arguments focusing on different morals and ask liberals and conservatives to evaluate the impact of these arguments.
Outcome: The proposed system generates arguments focusing on different morals, and the results are compared with existing arguments.
Probing Narrative Morals: A New Character-Focused MFT Framework for Use with Large Language Models (2025.emnlp-main)

Copied to clipboard

Challenge: Existing methods to categorize moral foundations in storytelling are limited.
Approach: They propose a character-centric method to quantify moral foundations in storytelling using large language models and a novel Moral Foundations Character Action Questionnaire to validate their approach against human annotations.
Outcome: The proposed method validates against human annotations and then applies to 2,697 folktales from 55 countries.
Text-based inference of moral sentiment change (D19-1)

Copied to clipboard

Challenge: Existing work in NLP treats moral sentiment as a flat classification problem, but our framework probes moral sentiment change at multiple levels and captures moral dynamics concerning relevance, polarity, and finegrained categories informed by Moral Foundations Theory.
Approach: They propose a text-based framework that exploits implicit moral biases learned from diachronic word embeddings to probe moral sentiment change over a long historical period.
Outcome: The proposed framework supports inferences of historical shifts in moral sentiment toward concepts such as slavery and democracy over centuries at three incremental levels: moral relevance, moral polarity, and fine-grained moral dimensions.
What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric (2023.acl-long)

Copied to clipboard

Challenge: Existing methods to analyze whether a text classifier learns the domain-specific expression of moral language are lacking.
Approach: They propose a method to compare a supervised classifier’s representation of moral rhetoric across domains by exploring similarities and differences between moral concepts and domains.
Outcome: The proposed method compares a supervised classifier’s representation of moral rhetoric across domains and domains.
MoVa: Towards Generalizable Classification of Human Morals and Values (2025.emnlp-main)

Copied to clipboard

Challenge: Identifying human morals and values embedded in language is essential to empirical studies of communication.
Approach: They propose a framework for generalizable classification of human morals and values . they recommend a classification strategy that scores all related concepts simultaneously .
Outcome: The proposed method outperforms fine-tuned models across domains and frameworks.
A Survey on Modelling Morality for Text Analysis (2024.findings-acl)

Copied to clipboard

Challenge: Recent work on modelling morality in text has garnered increasing attention due to its complexity and complexity.
Approach: They provide a systematic review of recent work on modelling morality in text . they discuss challenges and research gaps in the area of NLP .
Outcome: The authors present their work on the modelling of morality in text, which has garnered increasing attention in recent years.
Adaptable Moral Stances of Large Language Models on Sexist Content: Implications for Society and Gender Discourse (2024.emnlp-main)

Copied to clipboard

Challenge: Using large language models, large language model learning has become more integrated into our daily lives, making it increasingly important to ensure they reflect ethical and equitable values.
Approach: They assess how LLMs can apply moral reasoning to both criticize and defend sexist language by evaluating their models and evaluating the moral foundations cited by them.
Outcome: The models show they can provide comprehensible and contextually relevant text for understanding diverse views on how sexism is perceived.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations