Institution
Cyber University
Education•Fukuoka, Japan•
About: Cyber University is a education organization based out in Fukuoka, Japan. It is known for research contribution in the topics: The Internet & Web application. The organization has 113 authors who have published 259 publications receiving 2139 citations.
Topics: The Internet, Web application, GF(2), Multiplication, Cloud testing
Papers published on a yearly basis
Papers
TL;DR: The Bidirectional Encoder Representations from Transformers model (BERT) model is applied to detect fake news by analyzing the relationship between the headline and the body text of news and is determined that the deep-contextualizing nature of BERT is best suited for this task and improves the 0.14 F-score over older state-of-the-art models.
Abstract: News currently spreads rapidly through the internet. Because fake news stories are designed to attract readers, they tend to spread faster. For most readers, detecting fake news can be challenging and such readers usually end up believing that the fake news story is fact. Because fake news can be socially problematic, a model that automatically detects such fake news is required. In this paper, we focus on data-driven automatic fake news detection methods. We first apply the Bidirectional Encoder Representations from Transformers model (BERT) model to detect fake news by analyzing the relationship between the headline and the body text of news. To further improve performance, additional news data are gathered and used to pre-train this model. We determine that the deep-contextualizing nature of BERT is best suited for this task and improves the 0.14 F-score over older state-of-the-art models.
247 citations
TL;DR: It is confirmed that qualified information and services of O2O MSAs positively affect both perceived privacy protection and customer satisfaction, which finally lead to customer loyalty through the lens of the information systems success model.
158 citations
TL;DR: In this paper, the authors investigated online students' acceptance of mobile learning and its influence on learning achievement using an information system success and extended technology acceptance model (TAM) to test the structure of individual, social, and systemic factors influencing mobile learning acceptance, and how said acceptance influences learning satisfaction and achievement.
Abstract: This study investigates online students’ acceptance of mobile learning and its influence on learning achievement using an information system success and extended technology acceptance model (TAM). Structural equation modeling was used to test the structure of individual, social, and systemic factors influencing mobile learning’s acceptance, and how said acceptance influences learning satisfaction and achievement. Unlike earlier TAM-related research that did not provide a broad view of technological acceptance and its impact on learning activities, the present study’s results highlight the relationship between behavioral intention/learning satisfaction and learning achievement. Additionally, this study tests the theoretical model of successful mobile learning by empirically accepting mobile learning management systems. The findings further imply that students at online universities have started to accept mobile technology as a new learning tool; consequently, its acceptance has influenced their learning achievement both directly and indirectly. These discoveries should facilitate a better understanding of students’ usage of mobile learning systems in higher education, and provide timely guidance for its development and implementation.
156 citations
TL;DR: In the early half of the Earth history, the felsic continental crust on the surface which formed in an intra-oceanic environment has mostly been subducted into the deep mantle, except in the rare case of parallel arc collision.
142 citations
141 citations
Authors
Showing all 113 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Shigeichi Hirasawa | 16 | 192 | 1432 |
| Norihiro Kamide | 12 | 125 | 585 |
| Young-Ho Park | 11 | 48 | 328 |
| Sangwon Park | 9 | 38 | 1243 |
| Jieun Kim | 8 | 11 | 247 |
| Ul Soon Lee | 6 | 11 | 442 |
| Daiki Koizumi | 5 | 15 | 87 |
| Myonghyang Lee | 5 | 18 | 69 |
| Minseok Kang | 5 | 8 | 160 |
| Bong-Hwa Hong | 5 | 41 | 109 |
| Kwanyong Lee | 5 | 13 | 90 |
| Tomowo Ozawa | 5 | 8 | 195 |
| Hye-Jeong Hwang | 5 | 17 | 56 |
| Jeonghae Hwang | 5 | 17 | 81 |
| H. Senshu | 4 | 16 | 231 |
Related Institutes (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2023 | 1 |
| 2021 | 13 |
| 2020 | 14 |
| 2019 | 15 |
| 2018 | 13 |
| 2017 | 7 |