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Identifying Morality Frames in Political Tweets using Relational Learning
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In this article, the authors introduce a representation framework for organizing moral attitudes directed at different entities, and propose a relational learning model to predict moral attitudes towards entities and moral foundations jointly.Abstract:
Extracting moral sentiment from text is a vital component in understanding public opinion, social movements, and policy decisions. The Moral Foundation Theory identifies five moral foundations, each associated with a positive and negative polarity. However, moral sentiment is often motivated by its targets, which can correspond to individuals or collective entities. In this paper, we introduce morality frames, a representation framework for organizing moral attitudes directed at different entities, and come up with a novel and high-quality annotated dataset of tweets written by US politicians. Then, we propose a relational learning model to predict moral attitudes towards entities and moral foundations jointly. We do qualitative and quantitative evaluations, showing that moral sentiment towards entities differs highly across political ideologies.read more
Citations
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Proceedings ArticleDOI
Learning to Adapt Domain Shifts of Moral Values via Instance Weighting
TL;DR: This is the first study to quantify impacts of moral shifts, propose adaptive framework to model the shifts, and conduct a case study to model COVID-19 vaccine-related behaviors from moral values.
Journal ArticleDOI
Toxicity in Evolving Twitter Topics
TL;DR: In this paper , a Dynamic Topic Evolution Model (DyTEM) based on a corpus of collected tweets is constructed, which leverages a combination of traditional static Topic Modelling approaches and sentence embeddings using sBERT, a state-of-the-art sentence transformer.
Journal ArticleDOI
The presentation of South African politicians in The Times newspaper column “On the Contrary”: 2012-2017
Witness Roya,Sandiso Ngcobo +1 more
TL;DR: In this paper , the authors examined South African politicians' re-presentation in On the Contrary column, which appeared in The Times newspaper from 2012 to 2017, by employing the framing theory and critical discourse analysis (CDA) as research tools to assess the columnists' objectivity and bias.
Proceedings ArticleDOI
Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervision
TL;DR: This article proposed a minimally supervised multi-task learning framework for understanding messaging on Facebook related to the COVID vaccine by identifying ad themes and moral foundations and performed a more nuanced thematic analysis of messaging tactics of vaccine campaigns on social media so that policymakers can make better decisions on pandemic control.
References
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