Papers by Renato Ferreira Pinto Junior
Text-based inference of moral sentiment change (D19-1)
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| 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. |