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==The Product Space network==

==The Product Space network==

A network representation of the proximity matrix helps to develop intuition about its structure by establishing a visualization in which traditionally subtle trends become easily identifiable.

A network representation of the proximity matrix helps to develop intuition about its structure by establishing a visualization in which traditionally subtle trends become easily identifiable.

A network representation of the proximity matrix helps to develop intuition about its structure by establishing a visualization in which traditionally subtle trends become easily identifiable.

A network representation of the proximity matrix helps to develop intuition about its structure by establishing a visualization in which traditionally subtle trends become easily identifiable.

===Maximum spanning tree===

===Maximum spanning tree===

The initial step in building a network representation of product relatedness (proximities) involved first generating a network framework. [[File:ProductSpaceMST.png|thumb|left|upright=2|The maximum spanning tree represents the first step in visualizing the Product Space network.]]Here, the maximum spanning tree (MST) algorithm built a network of the 775 product nodes and the 774 links that would maximize the network's total proximity value.

The initial step in building a network representation of product relatedness (proximities) involved first generating a network framework. [[File:ProductSpaceMST.png|thumb|left|upright=2|The maximum spanning tree represents the first step in visualizing the Product Space network.]]Here, the maximum spanning tree (MST) algorithm built a network of the 775 product nodes and the 774 links that would maximize the network's total proximity value.

The initial step in building a network representation of product relatedness (proximities) involved first generating a network framework. The maximum spanning tree represents the first step in visualizing the Product Space network.Here, the maximum spanning tree (MST) algorithm built a network of the 775 product nodes and the 774 links that would maximize the network's total proximity value.

The initial step in building a network representation of product relatedness (proximities) involved first generating a network framework. The maximum spanning tree represents the first step in visualizing the Product Space network.Here, the maximum spanning tree (MST) algorithm built a network of the 775 product nodes and the 774 links that would maximize the network's total proximity value.

构建产品相关性(邻近性)的网络表示的第一步涉及首先生成一个网络框架。最大生成树表示可视化 Product Space 网络的第一步。在这里，最大生成树(MST)算法建立了一个网络的775个产品节点和774个链接，将网络的总邻近值最大化。

构建产品相关性(邻近性)网络表示的第一步为生成一个网络框架。此处，最大生成树(MST)算法建立了一个网络的775个产品节点和774个链接，将网络的总邻近值最大化。

===Network layout===

===Network layout===

[[File:ProductSpaceFDSL.png|thumb|left|upright=2|The force-directed spring layout above includes the links from the MST and any edge with a proximity greater than 0.55. To achieve the final Product Space design, the dense clusters were manually untangled and attributes were added in terms of node/link size and color.]] The basic "skeleton" of the network is developed by imposing on it the strongest links which were not necessarily in the MST by employing a threshold on the proximity values; they chose to include all links of proximity greater than or equal to 0.55. This produced a network of 775 nodes and 1525 links. This threshold was chosen such that the network exhibited an average degree equal to 4, a common convention for effective [[network visualization]]s. With the framework complete, a force-directed spring algorithm was used to achieve a more ideal network layout. This algorithm considers each node to be a charged particle and the links are assumed to be springs; the layout is the resulting equilibrium, or relaxed, position of the system. Manual rearranging untangled dense clusters to achieve maximum aesthetic efficacy.

[[File:ProductSpaceFDSL.png|thumb|left|upright=2|The force-directed spring layout above includes the links from the MST and any edge with a proximity greater than 0.55. To achieve the final Product Space design, the dense clusters were manually untangled and attributes were added in terms of node/link size and color.]] The basic "skeleton" of the network is developed by imposing on it the strongest links which were not necessarily in the MST by employing a threshold on the proximity values; they chose to include all links of proximity greater than or equal to 0.55. This produced a network of 775 nodes and 1525 links. This threshold was chosen such that the network exhibited an average degree equal to 4, a common convention for effective [[network visualization]]s. With the framework complete, a force-directed spring algorithm was used to achieve a more ideal network layout. This algorithm considers each node to be a charged particle and the links are assumed to be springs; the layout is the resulting equilibrium, or relaxed, position of the system. Manual rearranging untangled dense clusters to achieve maximum aesthetic efficacy.

The force-directed spring layout above includes the links from the MST and any edge with a proximity greater than 0.55. To achieve the final Product Space design, the dense clusters were manually untangled and attributes were added in terms of node/link size and color. The basic "skeleton" of the network is developed by imposing on it the strongest links which were not necessarily in the MST by employing a threshold on the proximity values; they chose to include all links of proximity greater than or equal to 0.55. This produced a network of 775 nodes and 1525 links. This threshold was chosen such that the network exhibited an average degree equal to 4, a common convention for effective network visualizations. With the framework complete, a force-directed spring algorithm was used to achieve a more ideal network layout. This algorithm considers each node to be a charged particle and the links are assumed to be springs; the layout is the resulting equilibrium, or relaxed, position of the system. Manual rearranging untangled dense clusters to achieve maximum aesthetic efficacy.

The force-directed spring layout above includes the links from the MST and any edge with a proximity greater than 0.55. To achieve the final Product Space design, the dense clusters were manually untangled and attributes were added in terms of node/link size and color. The basic "skeleton" of the network is developed by imposing on it the strongest links which were not necessarily in the MST by employing a threshold on the proximity values; they chose to include all links of proximity greater than or equal to 0.55. This produced a network of 775 nodes and 1525 links. This threshold was chosen such that the network exhibited an average degree equal to 4, a common convention for effective network visualizations. With the framework complete, a force-directed spring algorithm was used to achieve a more ideal network layout. This algorithm considers each node to be a charged particle and the links are assumed to be springs; the layout is the resulting equilibrium, or relaxed, position of the system. Manual rearranging untangled dense clusters to achieve maximum aesthetic efficacy.

力导向的弹簧布局上面包括链接从 MST 和任何接近大于0.55的边缘。为了实现最终的 Product Space 设计，人工解除了稠密的集群，并根据节点/链接大小和颜色添加了属性。网络的基本”骨架”是通过对邻近值设定一个阈值，将不一定在最小安全系数中的最强链接强加于网络; 这些链接选择包括大于或等于0.55的所有邻近链接。这产生了一个由775个节点和1525个链接组成的网络。选择这个阈值使得网络的平均度等于4，这是有效的网络可视化的一个常见规则。随着框架的完成，一个力导向的弹簧算法被用来实现更理想的网络布局。该算法将每个节点视为带电粒子，并假定每个连杆为弹簧，布局为系统的平衡位置或松弛位置。手动重新排列整齐的密集集群，以获得最大的美学效果。

上面的力定向弹簧布局包括来自MST的连接和邻近度大于0.55的任何边缘。为了实现最终的产品空间设计，手动地解开密集聚类，并根据节点/链接的大小和颜色添加属性。该网络的基本”骨架”是通过使用邻近值的阈值将不一定在 MST 中的最强链接强加给它而形成的; 选择包括大于或等于0.55的所有邻近链接。这产生了一个由775个节点和1525个链接组成的网络。选择阈值使得网络的平均度等于4，这是有效网络可视化的一个常见规则。随着框架的完成，用一个力导向的弹簧算法实现更理想的网络布局。该算法将每个节点视为带电粒子，并假定每个连杆为弹簧，布局为系统的平衡位置或松弛位置。手动重新排列整齐的密集集群，以获得最大的美学效果。

===Node and link attributes===

===Node and link attributes===

A system of colors and sizing allows for simultaneous assessment of the network structure with other covariates. The nodes of the Product Space are colored in terms of product classifications performed by Leamer<ref>E. Leamer, ''Sources of Comparative Advantage: Theory and Evidence'' (MIT Press, Cambridge, MA, 1984).</ref> and the size of the nodes reflects the proportion of money moved by that particular industry in world trade. The color of the links reflects the strength of the proximity measurement between two products: dark red and blue indicate high proximity whereas yellow and light blue imply weaker relatedness.

A system of colors and sizing allows for simultaneous assessment of the network structure with other covariates. The nodes of the Product Space are colored in terms of product classifications performed by Leamer<ref>E. Leamer, ''Sources of Comparative Advantage: Theory and Evidence'' (MIT Press, Cambridge, MA, 1984).</ref> and the size of the nodes reflects the proportion of money moved by that particular industry in world trade. The color of the links reflects the strength of the proximity measurement between two products: dark red and blue indicate high proximity whereas yellow and light blue imply weaker relatedness.

还有其他类型的分类适用于产品空间方法论，如拉尔提出的按技术强度对产品进行分类的分类。

还有其他类型的分类适用于产品空间方法论，如拉尔提出的按技术强度对产品进行分类的分类。

==Properties of the Product Space==

==Properties of the Product Space==