A multi-layer network approach to modelling authorship influence on citation dynamics in physics journals
| Autor: | Frank Schweitzer, Vahan Nanumyan, Christoph Gote |
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| Rok vydání: | 2020 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Physics - Physics and Society Theoretical computer science Model selection Statistical parameter FOS: Physical sciences Computer Science - Social and Information Networks Probability and statistics Physics and Society (physics.soc-ph) 01 natural sciences Computer Science::Digital Libraries 010305 fluids & plasmas Dynamics (music) Physics - Data Analysis Statistics and Probability 0103 physical sciences Scalability Layer (object-oriented design) 010306 general physics Citation Network approach Data Analysis Statistics and Probability (physics.data-an) |
| DOI: | 10.48550/arxiv.2002.12147 |
| Popis: | We provide a general framework to model the growth of networks consisting of different coupled layers. Our aim is to estimate the impact of one such layer on the dynamics of the others. As an application, we study a scientometric network, where one layer consists of publications as nodes and citations as links, whereas the second layer represents the authors. This allows us to address the question of how characteristics of authors, such as their number of publications or number of previous coauthors, impacts the citation dynamics of a new publication. To test different hypotheses about this impact, our model combines citation constituents and social constituents in different ways. We then evaluate their performance in reproducing the citation dynamics in nine different physics journals. For this, we develop a general method for statistical parameter estimation and model selection that is applicable to growing multilayer networks. It takes both the parameter errors and the model complexity into account and is computationally efficient and scalable to large networks. |
| Databáze: | OpenAIRE |
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