Flows of Knowledge in Citation Networks

Renoust, Benjamin; Claver, Vivek; Baffier, Jean-François

doi:10.1007/978-3-319-50901-3_13

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…In addition to the GVNs, our centrality measures can also be applied to other empirical settings in which the data can be represented as input-output K –partite graphs with K distinct sets of nodes. This is the case, for example, of inter-firm networks in which the firms are connected along serial supply chains within or across countries (Coe et al 2008 ), or innovation networks in which pools of knowledge can combine and be transformed along generative processes leading to the production of new knowledge (Ernst and Kim 2002 ; Renoust et al 2017 ). Similarly, the process of financial intermediation between savers and borrowers lends itself to the analysis of the centrality of the economic actors located at the various stages of the financial processes (Battiston et al 2003 ).…”

Section: Discussionmentioning

confidence: 99%

Countries’ positions in the international global value networks: Centrality and economic performance

2017

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The international exchange of goods and services is increasingly organised along global value chains in which the various production stages are carried out at many different locations all over the world. A country can be seen as holding a central position in global trade to the extent that it is involved in a large number of economic transactions with alternative potential suppliers and has a wide access to different important markets. However, the centrality of countries’ positions in the international production of goods and services may vary according to the specific stages of the production process that countries occupy. Here we adopt a network-based perspective, and propose a novel three-faceted measure of centrality that captures countries’ distinct roles at the upstream, midstream, and downstream stages of the international production process. Findings suggest that rankings of countries based on our measures of centrality vary across production stages. While emerging and developing countries tend to secure central positions at upstream and midstream production stages, high-income countries tend to exert prevailing roles at downstream stages. Moreover, rankings based on our measures differ from alternative rankings obtained from traditional measures of market power simply reflecting aggregate trade values. This is especially the case within more traditional industries, such as Textiles and Apparel, in which small and less developed countries can play relevant roles at various stages of the production process.Electronic supplementary materialThe online version of this article (doi:10.1007/s41109-017-0041-4) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Countries’ positions in the international global value networks: Centrality and economic performance

2017

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“…In this work, we extend our proposition to join the different views on knowledge production in a recursive framework (Renoust et al 2017) (which is covered in “Ascending flow in citation networks” section) to the analysis of multiplex citation networks and contribute with a new formalism, measures and experiments.…”

Section: Introductionmentioning

confidence: 99%

Multiplex flows in citation networks

2017

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Knowledge is created and transmitted through generations, and innovation is often seen as a process generated from collective intelligence. There is rising interest in studying how innovation emerges from the blending of accumulated knowledge, and from which path an innovation mostly inherits. A citation network can be seen as a perfect example of one generative process leading to innovation. However, the impact and influence of scientific publication are always difficult to capture and measure. We offer a new take on investigating how the knowledge circulates and is transmitted, inspired by the notion of “stream of knowledge”. We propose to look at this question under the lens of flows in directed acyclic graphs (DAGs). In this framework inspired by the work of Strahler, we can also account for other well known measures of influence such as the h-index. We propose then to analyze flows of influence in a citation networks as an ascending flow. From this point on, we can take a finer look at the diffusion of knowledge through the lens of a multiplex network. In this network, each citation of a specific work constitutes one layer of interaction. Within our framework, we design three measures of multiplex flows in DAGs, namely the aggregated, sum and selective flow, to better understand how citations are influenced. We conduct our experiments with the arXiv HEP-Th dataset, and find insights through the visualization of these multiplex networks.

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“…Significant resources for this task are represented by the networks of references between works and collaborations among personalities: for this reason, the fields where such features can be easily extracted have been extensively explored by both researchers and practitioners. In fact, thanks to the huge amount of publicly available data on citations between scientific papers, the majority of studies on this task concern scientific publications: such networks have been studied to analyze their structures (Sinatra et al 2015), to find innovation trends (Renoust et al 2016; Bioglio et al 2017), and to quantify the impact of papers and authors (Kaur et al 2015; Petersen et al 2014). The most known outcomes of this kind of research are the measures proposed to estimate the scientific production, such as the highly diffused (and discussed) Hirsch’s h-index (Hirsch 2005).…”

Section: Related Workmentioning

confidence: 99%

Identification of key films and personalities in the history of cinema from a Western perspective

Bioglio

Pensa

2018

Appl Netw Sci

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The success of a film is usually measured through its box-office revenue or through the opinion of professional critics; such measures, however, may be influenced by external factors, such as advertisement or trends, and are not able to capture the impact of a film over time. Thanks to the recent availability of data on references among movies, some researchers have started to use citations patterns as an alternative method for ranking movies. In this paper, we propose a novel ranking method for films based on the network of references among movies, calculated by combining four well known centrality indexes: in-degree, closeness, harmonic and PageRank. Our objective is to measure the success of a movie by accounting how much it has influenced other movies produced after its release, from both the artistic and the economic point of view. We apply our method on a subset of the IMDb (Internet Movie Database) citation network consisting of around 47,000 international movies, and we derive a list of films that can be considered milestones in the history of cinema. For each movie we also collect data on its year of release, genres and countries of production, to analyze trends and patterns in the film industry according to such features. We also collect data on 20,000 directors and almost 400,000 performers (actors and actresses), and we use the network of references and our score of movies for evaluating their career, and for ranking them. Since the IMDb dataset we employ is highly biased toward European and North American movies and personalities, our findings can be considered relevant principally for Western culture.

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Flows of Knowledge in Citation Networks

Cited by 7 publications

References 24 publications

Countries’ positions in the international global value networks: Centrality and economic performance

Countries’ positions in the international global value networks: Centrality and economic performance

Multiplex flows in citation networks

Identification of key films and personalities in the history of cinema from a Western perspective

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