Search Results for author:
Found 11 papers, 6 papers with code
ChatGPT Rates Natural Language Explanation Quality Like Humans: But on Which Scales?
Our results show that ChatGPT aligns better with humans in more coarse-grained scales.
Understanding News Thumbnail Representativeness by Counterfactual Text-Guided Contrastive Language-Image Pretraining
To serve the challenge, we introduce NewsTT, a manually annotated dataset of news thumbnail image and text pairs.
K-HATERS: A Hate Speech Detection Corpus in Korean with Target-Specific Ratings
This resource is the largest offensive language corpus in Korean and is the first to offer target-specific ratings on a three-point Likert scale, enabling the detection of hate expressions in Korean across varying degrees of offensiveness.
Detecting Contextomized Quotes in News Headlines by Contrastive Learning
Quotes are critical for establishing credibility in news articles.
Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus
A conversation corpus is essential to build interactive AI applications.
How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image
This study investigates how fake news uses a thumbnail for a news article with a focus on whether a news article's thumbnail represents the news content correctly.
Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text
Understanding who blames or supports whom in news text is a critical research question in computational social science.
How-to Present News on Social Media: A Causal Analysis of Editing News Headlines for Boosting User Engagement
To reach a broader audience and optimize traffic toward news articles, media outlets commonly run social media accounts and share their content with a short text summary.
"Trust me, I have a Ph.D.": A Propensity Score Analysis on the Halo Effect of Disclosing One's Offline Social Status in Online Communities
The results show that exposing academic degrees is likely to lead to higher audience votes as well as larger discussion size, compared to the users without the disclosed identities, in a community that covers peer-reviewed scientific articles.
Social and Information Networks
BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
In digital environments where substantial amounts of information are shared online, news headlines play essential roles in the selection and diffusion of news articles.
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume.
