Taehyun Ha
Biographic Data
| ID | 4981808 |
|---|---|
| NAME | Taehyun Ha |
| GIVEN NAMES | Taehyun |
| FAMILY NAME | Ha |
| SIGNATURE | HA T |
| AFFILIATIONS | Korea Institute of Science & Technology Information |
| ORCID | 0000-0003-3143-666X |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Automated weak signal detection and prediction using keyword network clustering and graph convolutional network
Weak signals are rarely identified in the initial stage of growth and appear significant over time, unlike strong signals clearly observed in past trends. Weak signals are important cues that need to be analyzed to rapidly and accurately predict changes in the uncertain future. Researchers have developed various methods for identifying cues that can be significantly used for prediction. However, in many cases, they heavily depend on the opinions …
Examining the effects of power status of an explainable artificial intelligence system on users’ perceptions
Contrary to the traditional concept of artificial intelligence, explainable artificial intelligence (XAI) aims to provide explanations for the prediction results and make users perceive the system as being reliable. However, despite its importance, only a few studies have investigated how the explanations of an XAI system should be designed. This study investigates how people attribute the perceived ability of XAI systems based on perceived attri…
An explainable artificial-intelligence-based approach to investigating factors that influence the citation of papers
Understanding of Majority Opinion Formation in Online Environments Through Statistical Analysis of News, Documentary, and Comedy YouTube Channels
Social networking services have been placed where people share opinions and information about various topics. These services allow users to express their opinions in direct (e.g., writing a comment or reply) and indirect ways (e.g., clicking a Like button). Based on commending, replying, and liking activities, users construct majority opinions in online environments. Previous studies examined perceptual and behavioral characteristics in the circu…
Automated weak signal detection and prediction using keyword network clustering and graph convolutional network
Weak signals are rarely identified in the initial stage of growth and appear significant over time, unlike strong signals clearly observed in past trends. Weak signals are important cues that need to be analyzed to rapidly and accurately predict changes in the uncertain future. Researchers have developed various methods for identifying cues that can be significantly used for prediction. However, in many cases, they heavily depend on the opinions …
Examining the effects of power status of an explainable artificial intelligence system on users’ perceptions
Contrary to the traditional concept of artificial intelligence, explainable artificial intelligence (XAI) aims to provide explanations for the prediction results and make users perceive the system as being reliable. However, despite its importance, only a few studies have investigated how the explanations of an XAI system should be designed. This study investigates how people attribute the perceived ability of XAI systems based on perceived attri…
An explainable artificial-intelligence-based approach to investigating factors that influence the citation of papers
Understanding of Majority Opinion Formation in Online Environments Through Statistical Analysis of News, Documentary, and Comedy YouTube Channels
Social networking services have been placed where people share opinions and information about various topics. These services allow users to express their opinions in direct (e.g., writing a comment or reply) and indirect ways (e.g., clicking a Like button). Based on commending, replying, and liking activities, users construct majority opinions in online environments. Previous studies examined perceptual and behavioral characteristics in the circu…
Automated weak signal detection and prediction using keyword network clustering and graph convolutional network
Weak signals are rarely identified in the initial stage of growth and appear significant over time, unlike strong signals clearly observed in past trends. Weak signals are important cues that need to be analyzed to rapidly and accurately predict changes in the uncertain future. Researchers have developed various methods for identifying cues that can be significantly used for prediction. However, in many cases, they heavily depend on the opinions …
Computer Science (4 works) · Mathematics (3 works) · Psychology (3 works) · Affect (linguistics) (2 works) · Artificial Intelligence (2 works) · Artificial Intelligence (2 works) · Data mining (2 works) · Perception (2 works) · Advanced Text Analysis Techniques (1 works) · Applied Psychology (1 works)