1 code implementation • 23 May 2023 • Lucille Njoo, Chan Young Park, Octavia Stappart, Marvin Thielk, Yi Chu, Yulia Tsvetkov
Empowering language is important in many real-world contexts, from education to workplace dynamics to healthcare.
no code implementations • 18 May 2023 • Jihyung Moon, Dong-Ho Lee, Hyundong Cho, Woojeong Jin, Chan Young Park, Minwoo Kim, Jonathan May, Jay Pujara, Sungjoon Park
Previous approaches to detecting toxic language and norm violations have been primarily concerned with conversations from online forums and social media, such as Reddit and Twitter.
no code implementations • 15 May 2023 • Shangbin Feng, Chan Young Park, YuHan Liu, Yulia Tsvetkov
We focus on hate speech and misinformation detection, aiming to empirically quantify the effects of political (social, economic) biases in pretraining data on the fairness of high-stakes social-oriented tasks.
no code implementations • 24 May 2022 • Chan Young Park, Julia Mendelsohn, Anjalie Field, Yulia Tsvetkov
NLP research on public opinion manipulation campaigns has primarily focused on detecting overt strategies such as fake news and disinformation.
1 code implementation • Findings (EMNLP) 2021 • Chan Young Park, Julia Mendelsohn, Karthik Radhakrishnan, Kinjal Jain, Tushar Kanakagiri, David Jurgens, Yulia Tsvetkov
Online platforms and communities establish their own norms that govern what behavior is acceptable within the community.
1 code implementation • 31 Dec 2020 • Anjalie Field, Chan Young Park, Kevin Z. Lin, Yulia Tsvetkov
In this work, we present a methodology for analyzing Wikipedia pages about people that isolates dimensions of interest (e. g., gender), from other attributes (e. g., occupation).
no code implementations • 21 Oct 2020 • Chan Young Park, Xinru Yan, Anjalie Field, Yulia Tsvetkov
Specific lexical choices in narrative text reflect both the writer's attitudes towards people in the narrative and influence the audience's reactions.
1 code implementation • SEMEVAL 2020 • Hwijeen Ahn, Jimin Sun, Chan Young Park, Jungyun Seo
This paper describes our approach to the task of identifying offensive languages in a multilingual setting.
1 code implementation • EACL 2021 • Jimin Sun, Hwijeen Ahn, Chan Young Park, Yulia Tsvetkov, David R. Mortensen
Much work in cross-lingual transfer learning explored how to select better transfer languages for multilingual tasks, primarily focusing on typological and genealogical similarities between languages.
no code implementations • WS 2019 • Chan Young Park, Yulia Tsvetkov
In this paper, we introduce a phrase-based NMT model built upon continuous-output NMT, in which the decoder generates embeddings of words or phrases.