Analysis of reference and citation copying in evolving bibliographic networks

Pandey, Pradumn Kumar; Singh, Mayank; Goyal, Pawan; Mukherjee, Animesh; Chakrabarti, Soumen

doi:10.1016/j.joi.2019.101003

Cited by 7 publications

(2 citation statements)

References 22 publications

(43 reference statements)

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“…This model has very less number of parameters and fits with the real data much better than the traditional models. Yet another novel citation growth model called RefOrCite (Pandey et al, 2020) has been proposed recently where the authors allow copying from the references (out-edges) and citations (in-edges) of an article (as opposed to only references in the traditional setup). It is observed that RefOrCite model fits well with real compared to the previous models.…”

Section: Analyzing and Modeling The Citation Dynamicsmentioning

confidence: 99%

Mining the online infosphere: A survey

Adak

Chakraborty

Das

et al. 2022

WIREs Data Min & Knowl

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The evolution of Artificial Intelligence (AI)-based systems and applications have pervaded everyday life to make decisions that have a momentous impact on individuals and society. With the staggering growth of online data, often termed as the online infosphere, it has become paramount to monitor the infosphere to ensure social good as AI-based decisions are severely dependent. This survey aims to provide a comprehensive review of some of the most important research areas related to the infosphere, focusing on the technical challenges and potential solutions. The survey also outlines some of the important future directions. We begin by focussing on the collaborative systems that have emerged within the infosphere with a special thrust on Wikipedia. In the follow-up, we demonstrate how the infosphere has been instrumental in the growth of scientific citations and collaborations, thus fuelling interdisciplinary research. Finally, we illustrate the issues related to the governance of the infosphere, such as the tackling of the (a) rising hateful and abusive behavior and (b) bias and discrimination in different online platforms and news reporting.

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Section: Analyzing and Modeling The Citation Dynamicsmentioning

confidence: 99%

Mining the online infosphere: A survey

Adak

Chakraborty

Das

et al. 2022

WIREs Data Min & Knowl

Self Cite

View full text Add to dashboard Cite

show abstract

“…This model has very less number of parameters and fits with the real data much better than the traditional models. Yet another novel citation growth model called RefOrCite [106] have been proposed recently where the authors allow copying from the references (out-edges) and citations (in-edges) of an article (as opposed to only references in the traditional setup). It is observed that RefOrCite model fits well with real compared to the previous models.…”

Section: Analyzing and Modelling The Citation Dynamicsmentioning

confidence: 99%

Mining the online infosphere: A survey

Adak¹,

Chakraborty²,

Das³

et al. 2021

Preprint

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The evolution of AI-based system and applications had pervaded everyday life to make decisions that have momentous impact on individuals and society. With the staggering growth of online data, often termed as the Online Infosphere it has become paramount to monitor the infosphere to ensure social good as the AI-based decisions are severely dependant on it. The goal of this survey is to provide a comprehensive review of some of the most important research areas related to infosphere, focusing on the technical challenges and potential solutions. The survey also outlines some of the important future directions. We begin by discussions focused on the collaborative systems that have emerged within the infosphere with a special thrust on Wikipedia. In the follow up we demonstrate how the infosphere has been instrumental in the growth of scientific citations and collaborations thus fuelling interdisciplinary research. Finally, we illustrate the issues related to the governance of the infosphere such as the tackling of the (a) rising hateful and abusive behaviour and (b) bias and discrimination in different online platforms and news reporting. * The first nine authors have been arranged based on family names and have equal contributions.1 https://en.wikipedia.org/wiki/Infosphere

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Relational hyperevent models for the coevolution of coauthoring and citation networks

Lerner,

Hâncean,

Lomi

2024

Journal of the Royal Statistical Society Series A: Statistics in Society

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The development of appropriate statistical models has lagged behind the ambitions of empirical studies analysing large scientific networks—systems of publications connected by citations and authorship. Extant research typically focuses on either paper citation networks or author collaboration networks. However, these networks involve both direct relationships, as well as broader dependencies between references linked by multiple citation paths. In this work, we extend recently developed relational hyperevent models to analyse networks characterized by complex dependencies across multiple network modes. We introduce new covariates to represent theoretically relevant and empirically plausible mixed-mode network configurations. This model specification allows testing hypotheses that recognize the polyadic nature of publication data, while accounting for multiple dependencies linking authors and references of current and prior papers. We implement the model using open-source software to analyse publicly available data on a large scientific network. Our findings reveal a tendency for subsets of papers to be cocited, indicating that the impact of these papers may be partly due to endogenous network processes. More broadly, the analysis shows that models accounting for both the hyperedge structure of publication events and the interconnections between authors and references significantly enhance our understanding of the mechanisms driving scientific production and impact.

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Analysis of reference and citation copying in evolving bibliographic networks

Cited by 7 publications

References 22 publications

Mining the online infosphere: A survey

Mining the online infosphere: A survey

Mining the online infosphere: A survey

Relational hyperevent models for the coevolution of coauthoring and citation networks

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