Using weighted k-means to identify Chinese leading venture capital firms incorporating with centrality measures

Yang, Hu; Luo, Jar‐Der; Fan, Ying; Zhu, Lei

doi:10.1016/j.ipm.2019.102083

Cited by 20 publications

(9 citation statements)

References 49 publications

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“…As following steps, we want to apply the GCMN centrality to other case studies to attest its effectiveness and compare the centrality to other group-based centrality measures [Agneessens et al, 2017, Borgatti and Everett, 2007, Hsieh and Magee, 2010, Yang et al, 2020.…”

Section: Discussionmentioning

confidence: 99%

“…Group-based strategies are a viable option in these situations. A case study presents a group-based approach based on the weighted k-means to rank venture capital firms in the Chinese investment market as an alternative strategy [Yang et al, 2020]. Previous authors propose a way to generalize block-modeling for hierarchical decomposition, using the k-means method to decompose a social network into groups of nodes having the existence of congruent profiles of dissimilarities with other nodes as a criterion [Hsieh and Magee, 2010].…”

Section: Related Workmentioning

confidence: 99%

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A Group-Based Centrality for Undirected Multiplex Networks: A Case Study of the Brazilian Car Wash Operation

Figueiredo

Nakamura

2021

IEEE Access

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One challenging issue in information science, biological systems, and many other fields is determining the most central or relevant networked systems agents. These networks usually describe scenarios using nodes (objects) and edges (the objects' relations). The so-called standard centrality measures aim to solve this kind of challenge, ranking the nodes by their supposed relevance and elect the most relevant nodes. This problem becomes more challenging when one single network is not enough to depict the whole scenario. In these cases, we can work with multiplex networks characterized by a set of network layers, each describing interrelationships that can change depending on external factors, e.g., time. This paper proposes a new centrality measure, the Group-based Centrality for Undirected Multiplex Networks, to find the most relevant nodes in an undirected multiplex network. As a case study, we use a Brazilian corruption investigation known as the Car Wash Operation. Our proposed centrality outperforms well-known centrality methods such as betweenness, eigenvector, weighted degree, Multiplex PageRank, closeness, and crosslayer degree centrality.INDEX TERMS group-based centrality measures, multiplex centrality measures, multiplex networks.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Group-Based Centrality for Undirected Multiplex Networks: A Case Study of the Brazilian Car Wash Operation

Figueiredo

Nakamura

2021

IEEE Access

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“…As medidas de centralidade podem ter desvantagens na tarefa de identificar os nós mais significativos de uma rede complexa no caso de cenários nos quais as decisões são baseadas em vários critérios. Uma estratégia alternativa de avaliação pode ser, por exemplo, ranquear nós baseada em grupos [Yang et al 2020]. O modelo NDNS tem um foco semelhante, ou seja, classifica os nós em uma estratégia hierárquica baseada em grupos, como uma alternativa às medidas de centralidade.…”

Section: Redes Complexasunclassified

Usando Análises Sociais Na Identificação De Nós Relevantes Em Um Cenário Multirredes: Operação Licitante Fantasma, Um Estudo De Caso / Using Social Analysis to Identify Relevant Nodes in a Multi-Network Scenario: The Ghost Bidder Operation, a Case Study

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Nakamura

Felix

et al. 2020

BJD

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“…And leading VC institutions also can act as bridges for resources and investment skills exchange, as they are usually hub nodes in the syndication network [ 19 ]. The ecosystem of VC market is way more complicated than a leader-follower structure, but most previous studies only focus on identifying leading VC institutions [ 22 , 23 , 24 ], and they usually do not have an objective criterion for identifying other groups of VC institutions. For example, Batjargal et al [ 22 ] analyzed empirical data to reveal investment patterns associated with leading VC institutions.…”

Section: Introductionmentioning

confidence: 99%

Unveiling Latent Structure of Venture Capital Syndication Networks

Yang

et al. 2022

Entropy

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Venture capital (VC) is a form of private equity financing provided by VC institutions to startups with high growth potential due to innovative technology or novel business models but also high risks. To against uncertainties and benefit from mutual complementarity and sharing resources and information, making joint-investments with other VC institutions on the same startup are pervasive, which forms an ever-growing complex syndication network. Attaining objective classifications of VC institutions and revealing the latent structure of joint-investment behaviors between them can deepen our understanding of the VC industry and boost the healthy development of the market and economy. In this work, we devise an iterative Loubar method based on the Lorenz curve to make objective classification of VC institutions automatically, which does not require setting arbitrary thresholds and the number of categories. We further reveal distinct investment behaviors across categories, where the top-ranked group enters more industries and investment stages with a better performance. Through network embedding of joint investment relations, we unveil the existence of possible territories of top-ranked VC institutions, and the hidden structure of relations between VC institutions.

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Using weighted k-means to identify Chinese leading venture capital firms incorporating with centrality measures

Cited by 20 publications

References 49 publications

A Group-Based Centrality for Undirected Multiplex Networks: A Case Study of the Brazilian Car Wash Operation

A Group-Based Centrality for Undirected Multiplex Networks: A Case Study of the Brazilian Car Wash Operation

Usando Análises Sociais Na Identificação De Nós Relevantes Em Um Cenário Multirredes: Operação Licitante Fantasma, Um Estudo De Caso / Using Social Analysis to Identify Relevant Nodes in a Multi-Network Scenario: The Ghost Bidder Operation, a Case Study

Unveiling Latent Structure of Venture Capital Syndication Networks

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