Using Social Network Analysis to Investigate the Potential of Innovation Networks: Lessons Learned from NASA's International Space Apps Challenge

Senghore, Fatima; Campos-Náñez, Enrique; Fomin, Pavel; Wasek, James S.

doi:10.1016/j.procs.2014.03.047

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…The above data indicate the topic of "network attack" has possessed the tendency of network concentration although the tendency is not significant. Senghore et al (2014) used social network analysis metrics including degree, degree distribution, degree correlations and density to understand the structure of and relationships for NASA's International Space, however, neglected nodes' interactive ability and independence. Guo and Zhang (2019) analyzed the degree of nodes' influence in a low density network and predicted the affect between the center nodes and normal nodes.…”

Section: Centrality Analysismentioning

confidence: 99%

Public opinion information dissemination in mobile social networks – taking Sina Weibo as an example

Wang

Xing

Wei

et al. 2020

IDD

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Purpose Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks. Design/methodology/approach This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals. Findings The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet. Social implications The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination. Originality/value This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”

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Section: Centrality Analysismentioning

confidence: 99%

Public opinion information dissemination in mobile social networks – taking Sina Weibo as an example

Wang

Xing

Wei

et al. 2020

IDD

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“…al. employed this model to empirically test the innovation success probability of NASA International Space Application Challenge Project, in which the authors analyzed the influences of innovation promotion and inhibition factors to the project's innovation process and resulting success, and theoretically revealed the dynamic mechanism of innovation process to its results [13]. Unfortunately, this model has not been testified in the enterprise innovation of agricultural industrial clusters.…”

Section: The Relations Between Kibs Embeddedness and The Enterprmentioning

confidence: 99%

Model of KIBS Embedding Driving Enterprises' Technology Innovation Among Agricultural Industrial Clusters

Chen¹,

Lu²,

Hao³

2016

Proceedings of the 2016 International Symposium on Business Cooperation and Development

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Abstract-In the Belt and Road strategy, innovation is very important for Chinese agricultural enterprises going out. KIBS Embedding, playing the role of intermediary, has been influencing the current innovation of cluster enterprises by its interaction with these entities. However, the existing research on KIBS embeddedness into industrial clusters focuses on that of manufacturing industry rather than agricultural industry. Therefore, the authors try to construct the model of KIBS embeddedness influencing the technology innovation among the agricultural industrial cluster, based on the concept model of complementary effects by industrial cluster and strategic alliance network to enterprises' technology innovation.

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“…The history of SNA dates to the 1930s (Moreno, 1953) however, it was not until 1954 that the term "social network analysis" was formalised into a theoretical perspective including concepts from graph theory, statistics, and probability. SNA has been used to study complex social interactions in various fields, for instance, healthcare (Chambers, Wilson, Thomson, & Harden, 2012), communication (Haythornthwaite, 1996), education (Aviv, Erlich, Ravid, & Geva, 2003), economics (Granovetter, 2005), political science (Ward, Stovel, & Sacks, 2011), and engineering (Senghore, Campos-Nanez, Fomin, & Wasek, 2014).…”

mentioning

confidence: 99%

Social Network Analysis and Online Learning Communities in Higher Education: A Systematic Literature Review

Jan

Vlachopoulos

Parsell

2019

OLJ

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This paper presents the results of a systematic literature review which sets out to explore the use of social network analysis (SNA) for investigating learning communities specifically, communities of practice (CoP) and community of inquiry (CoI) in higher education online learning (HEOL). The impetus for such a review originated from the reliance on extensive and time-consuming qualitative analysis typically required in research involving the CoP and CoI frameworks. The review consolidates and synthesizes existing research in HEOL in search of a methodological framework for structurally evaluating a CoP and/or CoI using SNA. We identified a handful of studies that integrate SNA measures and key structural components of the CoP and CoI frameworks and examined: SNA measures and corresponding theoretical components used; other analytical techniques used; limitations and; suggestions for further research. The selected studies reported disparate findings in terms of the relationship between SNA measures and the CoP and/or CoI components. The review also highlighted the need to complement SNA with a qualitative analytical technique. Therefore, whether SNA has the potential to be used as a stand-alone technique for structurally identifying communities remains to be seen. We also find a lack of consideration to attributional and performance variables in existing studies. In conclusion, we propose further research and the development of a fully integrated methodological framework which uses SNA to structurally evaluate a CoP and CoI.

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Using Social Network Analysis to Investigate the Potential of Innovation Networks: Lessons Learned from NASA's International Space Apps Challenge

Cited by 5 publications

References 16 publications

Public opinion information dissemination in mobile social networks – taking Sina Weibo as an example

Public opinion information dissemination in mobile social networks – taking Sina Weibo as an example

Model of KIBS Embedding Driving Enterprises' Technology Innovation Among Agricultural Industrial Clusters

Social Network Analysis and Online Learning Communities in Higher Education: A Systematic Literature Review

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