相关论文: Identifying Morality Frames in Political Tweets us…

News outlets are a primary source for many people to learn what is going on in the world. However, outlets with different political slants, when talking about the same news story, usually emphasize various aspects and choose their language…

Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational methods in Natural Language Processing (NLP) have been used…

Moral foundations theory explains variations in moral behavior using innate moral foundations: Care, Fairness, Ingroup, Authority, and Purity, along with experimental supports. However, little is known about the roles of and relationships…

Moral foundations theory helps understand differences in morality across cultures. In this paper, we propose a model to predict moral foundations (MF) from social media trending topics. We also investigate whether differences in MF…

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 Foundations Theory proposes that individuals with conflicting political views base their behavior on different principles chosen from a small group of universal moral foundations. This study proposes using a set of widely accepted…

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 (Graham et al., 2009). People vary in the weight…

The moral foundations theory supports that people, across cultures, tend to consider a small number of dimensions when classifying issues on a moral basis. The data also show that the statistics of weights attributed to each moral dimension…

This study uses sentiment analysis and the Moral Foundations Theory (MFT) to characterise news content in social media and examine its association with user engagement. We employ Natural Language Processing to quantify the moral and…

In this paper, we study the moral framing of political content on Twitter. Specifically, we examine differences in moral framing in two datasets: (i) tweets from US-based politicians annotated with political affiliation and (ii) COVID-19…

Large Language Models (LLMs) have become increasingly incorporated into everyday life for many internet users, taking on significant roles as advice givers in the domains of medicine, personal relationships, and even legal matters. The…

Moral values play a fundamental role in how we evaluate information, make decisions, and form judgements around important social issues. Controversial topics, including vaccination, abortion, racism, and sexual orientation, often elicit…

An audience's prior beliefs and morals are strong indicators of how likely they will be affected by a given argument. Utilizing such knowledge can help focus on shared values to bring disagreeing parties towards agreement. In argumentation…

Language models (LMs) are known to represent the perspectives of some social groups better than others, which may impact their performance, especially on subjective tasks such as content moderation and hate speech detection. To explore how…

This study enhances stance detection on social media by incorporating deeper psychological attributes, specifically individuals' moral foundations. These theoretically-derived dimensions aim to provide a comprehensive profile of an…

Ideological divisions in the United States have become increasingly prominent in daily communication. Accordingly, there has been much research on political polarization, including many recent efforts that take a computational perspective.…

This study investigates whether division on political topics is mapped with the distinctive patterns of language use. We collect a total 145,832 Reddit comments on the abortion debate and explore the languages of subreddit communities…

Society is showing signs of strong ideological polarization. When pushed to seek perspectives different from their own, people often reject diverse ideas or find them unfathomable. Work has shown that framing controversial issues using the…

Classifying moral values in user-generated text from social media is critical in understanding community cultures and interpreting user behaviors of social movements. Moral values and language usage can change across the social movements;…

Stance detection is the task of inferring viewpoint towards a given topic or entity either being supportive or opposing. One may express a viewpoint towards a topic by using positive or negative language. This paper examines how the stance…