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Seminar Title
Early Prediction of Academic Article Lifecycle Models Based on Multimodal Architecture
Year
112
Semester
2
Published date
2024-07-08
Seminar Name
Early Prediction of Academic Article Lifecycle Models Based on Multimodal Architecture
Seminar Name Other
All Author
Chia-Ling Chang, Yi- Lung Lin and Yi-Hung Liu
The Unit Of The Conference
Publisher
Meeting Name
The International Conference on Intelligent Science and Sustainable Development (ISASD 2024)
Meeting Place
東京,日本
Summary
The study of citation lifecycles in academic publications is crucial in scholarly research. Many studies use descriptive statistics or regression analyses to forecast citation outcomes, but they often don't fully combine textual data (like titles, abstracts, and keywords) with numerical data (such as impact factors and h-indexes). This research introduces an innovative multimodal model designed to predict early citation trajectories for scholarly articles, addressing this gap. We developed eight models to predict citations from the first to the eighth year based on 2017 data. Our lifecycle analysis shows that the model maintains high performance over multiple years, highlighting its robustness and adaptability. The results underscore the benefits of combining diverse data types for long-term predictive tasks, making our model a valuable tool for researchers and practitioners in Library and Information Science. This model significantly improves our ability to assess the early citation potential of academic papers, making it a valuable resource for researchers and policymakers in academic publishing. Additionally, to thoroughly explore bibliographic data, the study used LDA to investigate the topic distribution of library and information science publications in 2017.
Keyword
Life Cycle of Scholarly Articles;Citation Time Window;Early Prediction;Multimodal learning;Deep learning
Use Lang
English
Included in
Nature Of The Meeting
國際
On-campus Seminar Location
無
Seminar Time
20240708~20240711
Corresponding Author
Country
日本
Open Call for Papers
Publication style
Provenance