Eigenvector Centrality Based on Shared Research Topics in a Scientific Community

Volpentesta, Antonio Palmiro; Felicetti, Alberto Michele

doi:10.1007/978-3-642-15961-9_75

Cited by 3 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to calculate eigenvector centrality many algorithms have proposed in literature. Most of them are based on adaptations of the Hits (Hyperlink-Induced Topics Search) algorithm, introduced by Kleinberg, [32], [34].…”

Section: "A Node Is Important If It Is Connected With Other Importantmentioning

confidence: 99%

Identifying Opinion Leaders in Time-Dependent Commercial Social Networks

Volpentesta

Felicetti

2012

IFIP Advances in Information and Communication Technology

Self Cite

View full text Add to dashboard Cite

Abstract. The increasing amount of information flowing through commercial social networks offers clear advantages for companies who can take a valuable feedback from community actions. In particular, the identification of influential users in on-line social network can support companies in designing and targeting marketing campaigns, as influential gate-keepers and diffusers of information can ignite epidemics through word-of-mouth. In this paper, we model a time-dependent commercial social network as a time-varying weighted directed graph. Moreover, we propose an approach to determine opinion leaders and their contributions to a temporal business value, by taking into account behavioural and structural aspects of the commercial social network.

show abstract

Section: "A Node Is Important If It Is Connected With Other Importantmentioning

confidence: 99%

Identifying Opinion Leaders in Time-Dependent Commercial Social Networks

Volpentesta

Felicetti

2012

IFIP Advances in Information and Communication Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…state of the art search engines. Eigenvector centrality has been used to analyze for instance collaboration in scientific community (Volpentesta & Felicetti, 2010). Eigenvector centrality is defined as values of the first eigenvector (i.e.…”

Section: Accessmentioning

confidence: 99%

Complex Network Perspective on Collaboration in the ICT Standardization

Ali-Vehmas

2016

International Journal of Standardization Research

View full text Add to dashboard Cite

Standardization is a crucial enabler of global business of Information and Communications Technologies. Convergence of the underlying networking paradigms of licensed Mobile Communication and license exempted Internet has made progress but full integration is still far from being complete. For standardization professionals the unpredictable convergence makes decision-making and participation in standardization complicated. This study examines collaboration in five closely related standardization organizations working in this field during the years from 2003 to 2008. The results show similarities and differences in collaboration structures and behaviours reflecting the specific scope and context of each standardization organization. Furthermore, this study extends the use of social network analysis as a tool to the field of empirical standardization research. The results pave the way to better collaboration in standardization communities of converging Mobile Internet and beyond by providing better visibility and new insights to standardization leaders, policy makers and users.

show abstract

“…Within the PRO-VE conferences two papers addressed the social network and the conceptual evolution of the PRO-VE community. In [6] the authors exploited the concept of eigenvector centrality starting from the papers proceedings (2005)(2006)(2007)(2008)(2009) and propose a weighted multi-hypergraph model to study the (eigenvector) centrally of PRO-VE authors and research topics. The model is roughly equivalent to our 2mode network being the concepts taken from reference models and some text processing made to identify concepts through the papers "keywords".…”

Section: Related Workmentioning

confidence: 99%

A Retrospective Socio-Semantic Analysis of the PRO-VE Conferences

Soares

Almeida

Ramalho

2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

View full text Add to dashboard Cite

Part 19: Knowledge Management in NetworksInternational audienceThe IFIP WG 5.5 Working Conferences on Virtual Enterprises (PRO-VE) has created, in 14 editions, a remarkable scientific and professional community intersecting several disciplines and resulting in a new one: collaborative networks. In this paper we present the results of a retrospective study of the conceptual system evolution of PRO-VE providing an instrument to reflect about the field’s past and future. Our approach was socio-semantic trying to devise the influence between the researchers social network and the evolution of the conceptual system. Firstly, we made a terminological analysis of every PRO-VE proceeding resulting in a picture of the main concepts used in each edition and their relative importance. Then, we used social network analysis techniques to conclude about the influence of the researchers on the conceptual system evolution. The results suggest a relatively stable set of concepts influenced by a network of core researchers. However, some marked evolution in the relative importance of the concepts can be identified

show abstract

Eigenvector Centrality Based on Shared Research Topics in a Scientific Community

Cited by 3 publications

References 14 publications

Identifying Opinion Leaders in Time-Dependent Commercial Social Networks

Identifying Opinion Leaders in Time-Dependent Commercial Social Networks

Complex Network Perspective on Collaboration in the ICT Standardization

A Retrospective Socio-Semantic Analysis of the PRO-VE Conferences

Contact Info

Product

Resources

About