Co-occurrence analysis of scientific documents in citation networks

Muppidi, Satish; Reddy, Kanamata

doi:10.3233/kes-200025

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…When explaining the knowledge mapping generated by Cit-eSpace, as shown in Table 1, the selection of core keywords of mine dust is judged by the value range of centrality (Chen 2017), and the clarity and clustering scale of clustering boundary are measured by the clustering module value and average silhouette degree (Chen 2017;Chen et al 2010). When explaining the knowledge mapping of discipline co-occurrence generated by Python (Muppidi and Reddy 2020), the size of the node indicates the frequency of the discipline, the color of the node indicates the category of the discipline clustering, the line between nodes indicates the co-occurrence relationship between two disciplines, and the thickness of the line is proportional to the frequency of co-occurrence. The number of publications rapidly increased from 108 in 2016 to 258 in 2021, with an annual average of about 203 publications (total, 1014), which was a 3.11-fold increase compared to the previous period.…”

Section: Methods Of Scientometric Analysismentioning

confidence: 99%

Spatial and temporal evolution of mine dust research: visual knowledge mapping analysis in Web of Science from 2001 to 2021

Zeng

Jiang

2023

Environ Sci Pollut Res

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Dust pollution control is the basic guarantee of mine safety production, which has been widely concerned by scholars. Based on a total of 1786 publications collected by the Web of Science Core Collection (WOSCC) from 2001 to 2021, this paper analyzes the spatial–temporal distribution characteristics, hot topics, and frontier trends of the international mine dust field during the past 20 years by using Citespace and VOSviewer knowledge graph technology. The research shows that the study of mine dust can be divided into three stages: initial period (2001 ~ 2008), stable transition period (2009 ~ 2016), and boom period (2017 ~ 2021). The journals and disciplines which belong to mine dust research mainly focus on environmental science and engineering technology. A stable core group of authors and institutions have been preliminarily formed in the dust research field. The main themes of the study contained the whole process of mine dust generation, transport, prevention, and control, as well as the consequences of disaster. At present, the hot research fields mainly focus on mine dust particle pollution, multi-stage dust prevention, and emission reduction technologies, and mine occupational protection, monitoring, and early warning. In the future, the research should focus on the mechanism of dust production and transportation, the theory of efficient prevention and control, the technology and equipment of precise prevention and control of dust, and the high-precision monitoring and early warning of dust concentration. Future research should be concerned with dust control in underground mines and deep concave open-pit mines with complicated and treacherous environments, and strengthen research institutions, interdisciplinary cooperation, and interaction so as to promote the integration and application of mine dust and automation, information, and intelligent technology.

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Section: Methods Of Scientometric Analysismentioning

confidence: 99%

Spatial and temporal evolution of mine dust research: visual knowledge mapping analysis in Web of Science from 2001 to 2021

Zeng

Jiang

2023

Environ Sci Pollut Res

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“…with an average citation generated per year of 86.17 and an average citation in each article of 5.02. Co-occurrence analysis is very useful for analyzing the research for find the keyword analysis pattern and the author, but it does not always to use among the author [31].…”

Section: Condition Artificial Intelligence Techonologies Research In ...mentioning

confidence: 99%

Digital Business Transformation: Analysis of the Effect Artificial Intelligence in E-Commerce’s Product Recommendation

Louis,

Noerlina,

Syahchari

2024

A.I.S.

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The purpose of this study is to determine whether artificial intelligence used in E-Commerce influences product recommendations for users. This study explains how much influence artificial intelligence on product recommendations supplied by E-commerce in terms of consumer behavior in making purchasing decisions. Research methods. This research used bibliometric analysis to find the mapping of this topic with articles period 2017 to 2023 from Scopus database. Of the 103 articles were showed by keyword and analyzing the articles according to the relate of the content about 29 articles were finally obtained. The research result is Artificial Intelligence has influence for E-commerce, recommendation system, decision support system, customer behaviour’s, and customer trust. Product recommendations have an impact on E-Commerce. Conclusion. However, from the literature review, founded that there are still a few journals discussing related to considerations to the implementation regarding the use of AI in e-commerce "Consumer behaviour", "Customer Trust", "Purchasing decisions". This study is also useful to generate additional AI-related research in e-commerce and unquestionably for a fresh subject will be covered especially in context of product recommendations on E-commerce.

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“…The authors substantiate the model using the example of citation dynamics for physics articles, identifying nonlinear citation dynamics, the nonlinearity of which is closely related to the network topology. • Citation networks were also the subject of research in [16], which analyzed co-citations on the Web of Science citation dataset. The model proposed by the authors takes into account the frequency of co-occurrence of the first author, the frequency of co-occurrence of other authors, network density, as well as triadic closure in the cocitation graph.…”

mentioning

confidence: 99%

Network Evolution Model with Preferential Attachment at Triadic Formation Step

Sidorov,

Emelianov,

Mironov

et al. 2024

Mathematics

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It is recognized that most real systems and networks exhibit a much higher clustering with comparison to a random null model, which can be explained by a higher probability of the triad formation—a pair of nodes with a mutual neighbor have a greater possibility of having a link between them. To catch the more substantial clustering of real-world networks, the model based on the triadic closure mechanism was introduced by P. Holme and B. J. Kim in 2002. It includes a “triad formation step” in which a newly added node links both to a preferentially chosen node and to its randomly chosen neighbor, therefore forming a triad. In this study, we propose a new model of network evolution in which the triad formation mechanism is essentially changed in comparison to the model of P. Holme and B. J. Kim. In our proposed model, the second node is also chosen preferentially, i.e., the probability of its selection is proportional to its degree with respect to the sum of the degrees of the neighbors of the first selected node. The main goal of this paper is to study the properties of networks generated by this model. Using both analytical and empirical methods, we show that the networks are scale-free with power-law degree distributions, but their exponent γ is tunable which is distinguishable from the networks generated by the model of P. Holme and B. J. Kim. Moreover, we show that the degree dynamics of individual nodes are described by a power law.

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Co-occurrence analysis of scientific documents in citation networks

Cited by 11 publications

References 18 publications

Spatial and temporal evolution of mine dust research: visual knowledge mapping analysis in Web of Science from 2001 to 2021

Spatial and temporal evolution of mine dust research: visual knowledge mapping analysis in Web of Science from 2001 to 2021

Digital Business Transformation: Analysis of the Effect Artificial Intelligence in E-Commerce’s Product Recommendation

Network Evolution Model with Preferential Attachment at Triadic Formation Step

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