Visualization of a directed network with focus on its hierarchy and circularity

Kichikawa, Yuichi; Iino, Takashi; Iyetomi, Hiroshi; Inoue, Hiroyasu

doi:10.1007/s42001-019-00031-1

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…We first construct a directed network [4], [5], [6] based on the relationships between influencers and followers, which contains 5,506 nodes and 42,770 edges, shown in Fig. 1.…”

Section: Visualization Of the Influence Networkmentioning

confidence: 99%

A Novel Exploration of Potential Music Influence Based on Graph Theory

Luo

Chen

2022

J. Phys.: Conf. Ser.

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Most artists have been influenced by their predecessors or peers in their lives, who brought them inspiration to form their own composing style and direction. This pattern is particularly important for the study of the developing trend of the music field. Based on the da ta which records the influence relationships of musicians over the years, we construct a directed influence network, reflecting the connection among musicians. Then from the perspective of the subnetwork, a synthetic appraisal model is put forward to quantify the influence of artists. In order to indicate its correctness and objectivity, the influence patterns between musicians and their works are further explored by analyzing the attributes of songs. Finally, for the music itself, the properties of the music are analyzed through standardized regression to obtain the characteristics that have the greatest impact on the music influence.

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“…We first construct a directed network [4], [5], [6] based on the relationships between influencers and followers, which contains 5,506 nodes and 42,770 edges, shown in Fig. 1.…”

Section: Visualization Of the Influence Networkmentioning

confidence: 99%

A Novel Exploration of Potential Music Influence Based on Graph Theory

Luo

Chen

2022

J. Phys.: Conf. Ser.

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“…The hierarchical dependence of data describing the volume of marketable food products carried out at the level of municipalities and wholesale trade at the level of regions has been noted repeatedly. Some noted the multilevel process (Sadigh et al, 2013) and the hierarchy of supply chain (Kichikawa et al, 2019); others noted the hierarchy of functional areas (Philbrick, 2005). Thus, on the one hand, the hierarchical relationship is manifested in the wholesale-retail-consumer sequence, in which revenue determines retail sales, and retail sales depend on the goods delivered in bulk.…”

Section: Problem Statementmentioning

confidence: 99%

Spatial Aspect In The Volume Of Marketable Food Products

Timiryanova¹

2021

European Proceedings of Social and Behavioural Sciences

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“…First, scientists point out that data is hierarchical, but in each case, different aspects of multi-layering may be highlighted. In supply chain studies, scientists assume that coordinating all parts of the supply chain is a multilevel process (Sadigh et al 2013) and the hierarchy of the production network emerged from the self-organization of the supply chain, which allows us to highlight the hierarchical supply chain (Kichikawa et al 2019). Hesse (2010) argues that gateways may play a distinct yet no longer dominant role in the hierarchy of centers within the framework of the theory of central places.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial Patterns of Production-Distribution-Consumption Cycle: The Specifics of Developing Russia

2020

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The existing body of academic literature reveals that production, distribution, and consumption might be both consistently connected and geographically scattered. This requires assessing the spatial order of production–distribution–consumption cycle, within which exploring of spatial relationship would be based on mutual dependence on each other’s of production, distribution and consumption. Hierarchical and spatial nesting of production, distribution, and consumption data allows us to apply hierarchical spatial autoregressive models (HSAR). The study was conducted on data from 2132 municipalities within 84 regions of the Russian Federation in 2018. The created models enabled distinguishing intraregional and interregional effects and highlighted the positive effect of spatial interactions in production volume. The calculations showed that population income, which determine the demand for goods are positively associated with production volume while relationship between manufacturing and wholesale is negative, resulting in revision of relations between wholesale and manufacturing enterprises and boosting ways of improvement the competitiveness of manufactured goods. The results allow us not only to enhance understanding of the spatial pattern of production–distribution–consumption cycle, but also to reveal new opportunities in the development of supply chain location policy.

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Visualization of a directed network with focus on its hierarchy and circularity

Cited by 7 publications

References 6 publications

A Novel Exploration of Potential Music Influence Based on Graph Theory

A Novel Exploration of Potential Music Influence Based on Graph Theory

Spatial Aspect In The Volume Of Marketable Food Products

Spatial Patterns of Production-Distribution-Consumption Cycle: The Specifics of Developing Russia

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