Measuring the social influences of scientist groups based on multiple types of collaboration relations

Jiang, Jiuchuan; Shi, Peng; An, Bo; Yu, Jianyong; Wang, Chongjun

doi:10.1016/j.ipm.2016.06.003

Cited by 26 publications

(11 citation statements)

References 34 publications

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“…Two parts of social influence, the possibility of impact between two users and the importance of each user, were discussed . Social influence of scientist groups was analyzed considering two general group types (hierarchical and nonhierarchical) and two general collaboration situations (the independently multiplex collaboration relationships and the correlated multiplex collaboration relationships) . Evental Affinity Propagation (TAP) was proposed to model the event‐level social influence on co‐author network …”

Section: Related Workmentioning

confidence: 99%

“…15 Social influence of scientist groups was analyzed considering two general group types (hierarchical and nonhierarchical) and two general collaboration situations (the independently multiplex collaboration relationships and the correlated multiplex collaboration relationships). 16 Evental Affinity Propagation (TAP) was proposed to model the event-level social influence on co-author network. 17 Most of previous methods only studied user network, eg, follower and followee network, and user behavior network.…”

Section: Related Workmentioning

confidence: 99%

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Finding influential users of web event in social media

Luo

Zhuge

2018

Concurrency and Computation

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Summary Users of social media have different influences on the evolution of a Web event. Finding influential users could benefit such information services as recommendation and market analysis. However, most of the existing methods are only based on social networks of users or user behaviors while the role of the contents contributed by users in social media is ignored. In fact, a Web event evolves with both user behaviors and the contents. This paper proposes an approach to find influential users by extracting user behavior network and association network of words within the contents and then uses PageRank algorithm and HITS algorithm to calculate the influence of users on the integration of two networks. The proposed approach is effective on several real‐world datasets.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Finding influential users of web event in social media

Luo

Zhuge

2018

Concurrency and Computation

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“…In previous works ( [22,23]), we present a collaboration network analysis as a management tool using publication data available in Lattes Platform from one Computer Science graduate program in Brazil, including a recommendation module for scientific partnerships. Besides, many international works are leading to interesting findings as in [24] that explores how collaboration in Computer Science evolved since 1960, measuring influences of scientist groups based on multiple types of collaboration [25], and a cross-disciplinary research work presenting a survey of scientific teamwork collaboration [26]. Nevertheless, there is a research gap concerning the Brazilian Computer Science graduate programs with intra-and inter-scientific collaboration analysis.…”

Section: Introductionmentioning

confidence: 99%

Scientific Collaboration Network Analysis: A Brazilian Computer Science Graduate Programs Case

Costa¹,

Nunes²,

Ralha³

2021

Preprint

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Scientific collaboration networks can present different views of researchers’ interaction. The analysis of these networks allows research transparency focusing on the understanding of how science evolves in different contexts. In this article, we present a scientific collaboration network analysis using social network metrics as average degree, connected components, betweenness and closeness centralities applied to five Brazilian Computer Science graduate programs. An online artifact built upon the design science research paradigm, namely SCI-synergy, was developed to ease the analysis involving publication data available on the Digital Bibliography & Library Project (DBLP) from the graduate program members allied to the Federal University of Minas Gerais (UFMG), the State University of São Paulo (USP), the Federal University of Rio Grande do Norte (UFRN), the Federal University of Amazonas (UFAM), and the University of Brasília (UnB). The objective is to analyze the scientific collaboration network of each program focusing on the researchers’ collaboration to understand patterns considering intra- and inter-program relationships. The analysis covers two database updates of 2019 and 2021. Results show that intra-program relationships are not always bigger among the highest-ranked programs in CAPES. Nevertheless, UFMG presents a greater total of cooperation among the five programs indicating research leadership and good inter-program collaboration patterns. We advocate that the collaboration network analysis using an online artifact can be useful to understand patterns of all the Brazilian Computer Science graduate programs to discover new research perspectives to be improved, avoided or even applied to other contexts.

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“…Researchers have utilized patent documents to analyze technology trends (Khasseh et al, 2017;Kim, Suh, & Park, 2008;Yoon & Park, 2004), perform tasks of technology forecasting (Chen et al, 2017;Daim et al, 2006;G. Kim & Bae, 2017;Kyebambe et al, 2017;Yoon & Park, 2005), investigate relations among scientists (Jiang et al, 2017), and undertake strategic technology planning (Joung & Kim, 2017;Lee, Kim, & Shin, 2017;Yu & Zhang, 2017). However, we still lack in a holistic understanding of technological change that considers four distinct but interrelated dimensions and evolutionary paths that lead to advances in a specific technology sector, i.e.…”

Section: Introductionmentioning

confidence: 99%

Capturing information on technology convergence, international collaboration, and knowledge flow from patent documents: A case of information and communication technology

Lee¹,

Kogler²,

Lee³

2019

Information Processing & Management

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Recent advances in data-driven research approaches offer new and exciting perspectives and insights across a spectrum scientific fields concerned with technological change and the socioeconomic impact thereof, while also providing the opportunity to address persistent gaps in existing theories. The present investigation suggests a novel approach to identify and analyse the evolution of technology sectors, in this case Information and Communications Technology (ICT), considering international collaboration patterns and knowledge flows and spillovers via information inputs derived from patent documents. The objective is to utilize and explore information regarding inventors' geo-location, technology sector classifications, and patent citation records to construct various types of networks. This, in turn, will open up avenues to discover the nature of evolutionary pathways in ICT technology trajectories, and also provide evidence of how the overall ICT knowledge space, as well as directional knowledge flows within the ICT space, evolved differently. It is expected that this datadriven inquiry will deliver intuitive results for decision makers seeking evidence for future resource allocation and who are interested in identifying well-suited collaborators for the development of potential next-generation technologies. Further, it will equip researchers in technology management, economic geography, or similar fields with a systematic approach to analyse evolutionary pathways of technological advancements and further enable them to exploit existing and develop new theories regarding technological change and its socioeconomic consequences.

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Measuring the social influences of scientist groups based on multiple types of collaboration relations

Cited by 26 publications

References 34 publications

Finding influential users of web event in social media

Finding influential users of web event in social media

Scientific Collaboration Network Analysis: A Brazilian Computer Science Graduate Programs Case

Capturing information on technology convergence, international collaboration, and knowledge flow from patent documents: A case of information and communication technology

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