Jin‐Cheon
Biographic Data
| ID | 6543143 |
|---|---|
| NAME | Jin‐Cheon |
| FAMILY NAME | Jin‐Cheon |
| SIGNATURE | CHEON J |
| AFFILIATIONS | Nanyang Technological University |
| ORCID | 0000-0002-2211-9382 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Examining scholarly communication on X (Twitter)
A Theory-Driven Approach to Fake News/Information Disorder Analysis and Explanation via Target-Based Emotion–Stance Analysis (Tesa) and Interpretive Graph Generation (IGG)
Information disorder (IDO) presents a persistent challenge to society, necessitating innovative approaches to understanding its dynamics beyond just merely detecting it. This study introduces a theory-driven framework that integrates advanced natural language processing (NLP) with deep learning, utilizing the target-based emotion–stance analysis (TESA) approach to analyze emotion and stance dynamics within IDO content. Complementing TESA, interac…
Who is mentioning Covid-19 articles on twitter? Classifying twitter users in the context of scholarly communication
Why are medical research articles tweeted? The news value perspective
Are automated accounts driving scholarly communication on Twitter? a case study of dissemination of Covid-19 publications
Influence diffusion detection using the influence style ( Infuse ) model
Blogs are readily available sources of opinions and sentiments that in turn could influence the opinions of the blog readers. Previous studies have attempted to infer influence from blog features, but they have ignored the possible influence styles that describe the different ways in which influence is exerted. We propose a novel approach to analyzing bloggers' influence styles and using the influence styles as features to improve the performance…
No prominent works on this page.
Influence diffusion detection using the influence style ( Infuse ) model
Blogs are readily available sources of opinions and sentiments that in turn could influence the opinions of the blog readers. Previous studies have attempted to infer influence from blog features, but they have ignored the possible influence styles that describe the different ways in which influence is exerted. We propose a novel approach to analyzing bloggers' influence styles and using the influence styles as features to improve the performance…
Are automated accounts driving scholarly communication on Twitter? a case study of dissemination of Covid-19 publications
Why are medical research articles tweeted? The news value perspective
Who is mentioning Covid-19 articles on twitter? Classifying twitter users in the context of scholarly communication
Examining scholarly communication on X (Twitter)
A Theory-Driven Approach to Fake News/Information Disorder Analysis and Explanation via Target-Based Emotion–Stance Analysis (Tesa) and Interpretive Graph Generation (IGG)
Information disorder (IDO) presents a persistent challenge to society, necessitating innovative approaches to understanding its dynamics beyond just merely detecting it. This study introduces a theory-driven framework that integrates advanced natural language processing (NLP) with deep learning, utilizing the target-based emotion–stance analysis (TESA) approach to analyze emotion and stance dynamics within IDO content. Complementing TESA, interac…
Computer Science (6 works) · Misinformation and Its Impacts (5 works) · Political science (4 works) · Internet privacy (3 works) · Psychology (3 works) · Scholarly communication (3 works) · Social media (3 works) · World Wide Web (3 works) · Data science (2 works) · Hate Speech and Cyberbullying Detection (2 works)