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20182022
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cs.CL20251 cited

Unveiling Affective Polarization Trends in Parliamentary Proceedings

Gili Goldin, Ella Rabinovich, Shuly Wintner

Recent years have seen an increase in polarized discourse worldwide, on various platforms. We propose a novel method for quantifying polarization, based on the emotional style of t…

cs.CL2025

An Annotation Scheme for Factuality and its Application to Parliamentary Proceedings

Gili Goldin, Shira Wigderson, Ella Rabinovich +1

Factuality assesses the extent to which a language utterance relates to real-world information; it determines whether utterances correspond to facts, possibilities, or imaginary si…

cs.CL2025

Strategies of Code-switching in Human-Machine Dialogs

Dean Geckt, Melinda Fricke, Shuly Wintner

Most people are multilingual, and most multilinguals code-switch, yet the characteristics of code-switched language are not fully understood. We developed a chatbot capable of comp…

cs.CL2022

Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching

Alissa Ostapenko, Shuly Wintner, Melinda Fricke +1

Natural language processing (NLP) models trained on people-generated data can be unreliable because, without any constraints, they can learn from spurious correlations that are not…

cs.CL2021

Machine Translation into Low-resource Language Varieties

Sachin Kumar, Antonios Anastasopoulos, Shuly Wintner +1

State-of-the-art machine translation (MT) systems are typically trained to generate the "standard" target language; however, many languages have multiple varieties (regional variet…

cs.CL2018

Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies

Anjalie Field, Doron Kliger, Shuly Wintner +3

Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and "fake news'". Here, we draw on two concepts from the political sci…