Marcell Nagy
Biographic Data
| ID | 3925808 |
|---|---|
| NAME | Marcell Nagy |
| GIVEN NAMES | Marcell |
| FAMILY NAME | Nagy |
| SIGNATURE | NAGY M |
| AFFILIATIONS | Budapest University of Technology and Economics |
| ORCID | 0000-0001-5666-7777 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Topicality boosts popularity
This study sheds light on interconnected topic dynamics across traditional news sources and social media platforms, emphasizing the influential role of topicality in shaping content popularity in social media. Using the Latent Dirichlet Allocation and BERTopic models, we define sets of 120 New York Times (NYT) topics to compare with 899,766 image-with-text memes from Reddit, showing that social media content aligns with many of the same topical p…
How to improve the predictive validity of a composite admission score? A case study from Hungary
An essential task in higher education is to construct a fair admission procedure. A great deal of research has been conducted on a central aspect of admission: predictive validity. However, to the best of our knowledge, this is the first study that investigates how the predictive validity of a composite admission score could be improved without redesigning the tests and introducing new measures. In this study, relying on the existing instruments …
Network classification-based structural analysis of real networks and their model-generated counterparts
Data-driven analysis of complex networks has been in the focus of research for decades. An important area of research is to study how well real networks can be described with a small selection of metrics, furthermore how well network models can capture the relations between graph metrics observed in real networks. In this paper, we apply machine-learning techniques to investigate the aforementioned problems. We study 500 real-world networks along…
Comprehensive analysis of the predictive validity of the university entrance score in Hungary
An important problem in higher education is to find the most suitable admission procedure that can distinguish between students with high academic potential and future dropouts. Admissions usually rely on pre-enrolment achievement measures; therefore, it is crucial that these selection criteria have high predictive validity on academic achievement. In this study, we use sophisticated statistical learning methods, such as receiver operating charac…
Network classification-based structural analysis of real networks and their model-generated counterparts
Data-driven analysis of complex networks has been in the focus of research for decades. An important area of research is to study how well real networks can be described with a small selection of metrics, furthermore how well network models can capture the relations between graph metrics observed in real networks. In this paper, we apply machine-learning techniques to investigate the aforementioned problems. We study 500 real-world networks along…
Comprehensive analysis of the predictive validity of the university entrance score in Hungary
An important problem in higher education is to find the most suitable admission procedure that can distinguish between students with high academic potential and future dropouts. Admissions usually rely on pre-enrolment achievement measures; therefore, it is crucial that these selection criteria have high predictive validity on academic achievement. In this study, we use sophisticated statistical learning methods, such as receiver operating charac…
Network classification-based structural analysis of real networks and their model-generated counterparts
Data-driven analysis of complex networks has been in the focus of research for decades. An important area of research is to study how well real networks can be described with a small selection of metrics, furthermore how well network models can capture the relations between graph metrics observed in real networks. In this paper, we apply machine-learning techniques to investigate the aforementioned problems. We study 500 real-world networks along…
How to improve the predictive validity of a composite admission score? A case study from Hungary
An essential task in higher education is to construct a fair admission procedure. A great deal of research has been conducted on a central aspect of admission: predictive validity. However, to the best of our knowledge, this is the first study that investigates how the predictive validity of a composite admission score could be improved without redesigning the tests and introducing new measures. In this study, relying on the existing instruments …
Topicality boosts popularity
This study sheds light on interconnected topic dynamics across traditional news sources and social media platforms, emphasizing the influential role of topicality in shaping content popularity in social media. Using the Latent Dirichlet Allocation and BERTopic models, we define sets of 120 New York Times (NYT) topics to compare with 899,766 image-with-text memes from Reddit, showing that social media content aligns with many of the same topical p…
Computer Science (3 works) · Psychology (3 works) · Clinical Psychology (2 works) · Medical Education and Admissions (2 works) · Predictive validity (2 works) · Psychometrics (2 works) · Social Psychology (2 works) · Advertising (1 works) · Artificial Intelligence (1 works) · Bioinformatics and Genomic Networks (1 works)