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A Geometric Representation of Collective Attention Flows.

Shi P, Huang X, Wang J, Zhang J, Deng S, Wu Y - PLoS ONE (2015)

Bottom Line: As a result, knowing how collective attention distributes and flows among different websites is the first step to understand the underlying dynamics of attention on WWW.And the patterns are stable across different periods.Thus, the overall distribution and the dynamics of collective attention on websites can be well exhibited by this geometric representation.

View Article: PubMed Central - PubMed

Affiliation: Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, China; School of Systems Science, Beijing Normal University, Beijing, China.

ABSTRACT
With the fast development of Internet and WWW, "information overload" has become an overwhelming problem, and collective attention of users will play a more important role nowadays. As a result, knowing how collective attention distributes and flows among different websites is the first step to understand the underlying dynamics of attention on WWW. In this paper, we propose a method to embed a large number of web sites into a high dimensional Euclidean space according to the novel concept of flow distance, which both considers connection topology between sites and collective click behaviors of users. With this geometric representation, we visualize the attention flow in the data set of Indiana university clickstream over one day. It turns out that all the websites can be embedded into a 20 dimensional ball, in which, close sites are always visited by users sequentially. The distributions of websites, attention flows, and dissipations can be divided into three spherical crowns (core, interim, and periphery). 20% popular sites (Google.com, Myspace.com, Facebook.com, etc.) attracting 75% attention flows with only 55% dissipations (log off users) locate in the central layer with the radius 4.1. While 60% sites attracting only about 22% traffics with almost 38% dissipations locate in the middle area with radius between 4.1 and 6.3. Other 20% sites are far from the central area. All the cumulative distributions of variables can be well fitted by "S"-shaped curves. And the patterns are stable across different periods. Thus, the overall distribution and the dynamics of collective attention on websites can be well exhibited by this geometric representation.

No MeSH data available.


The geometric representation of top 2200 websites.Sub figure A shows the geometric representation of the selected websites on October 10 in 2006. The node colors represent the categories of the websites and the node sizes are proportional to the traffics of the focus websites. The small figures in the bottom are the same representations for selected Adults websites in B, Education websites in C, and News Recreation websites in D.
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pone.0136243.g003: The geometric representation of top 2200 websites.Sub figure A shows the geometric representation of the selected websites on October 10 in 2006. The node colors represent the categories of the websites and the node sizes are proportional to the traffics of the focus websites. The small figures in the bottom are the same representations for selected Adults websites in B, Education websites in C, and News Recreation websites in D.

Mentions: Next, we select a strong connected sub-network containing 2200 websites from the top 4000 websites of the original network on October 10,2006 to be embeded into a 20 dimensional Euclidean space by using a reduced version of BigBang algorithm [35] (details can be referred to the method section) such that the Euclidean distance between any two nodes is as closed as possible to their flow distance. In this way, each node obtains a coordinate. To visualize this sub-network, we project all nodes into a two dimensional space by using the PCA method [37, 38] to reduce the dimensionality as shown in Fig 3.


A Geometric Representation of Collective Attention Flows.

Shi P, Huang X, Wang J, Zhang J, Deng S, Wu Y - PLoS ONE (2015)

The geometric representation of top 2200 websites.Sub figure A shows the geometric representation of the selected websites on October 10 in 2006. The node colors represent the categories of the websites and the node sizes are proportional to the traffics of the focus websites. The small figures in the bottom are the same representations for selected Adults websites in B, Education websites in C, and News Recreation websites in D.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4556699&req=5

pone.0136243.g003: The geometric representation of top 2200 websites.Sub figure A shows the geometric representation of the selected websites on October 10 in 2006. The node colors represent the categories of the websites and the node sizes are proportional to the traffics of the focus websites. The small figures in the bottom are the same representations for selected Adults websites in B, Education websites in C, and News Recreation websites in D.
Mentions: Next, we select a strong connected sub-network containing 2200 websites from the top 4000 websites of the original network on October 10,2006 to be embeded into a 20 dimensional Euclidean space by using a reduced version of BigBang algorithm [35] (details can be referred to the method section) such that the Euclidean distance between any two nodes is as closed as possible to their flow distance. In this way, each node obtains a coordinate. To visualize this sub-network, we project all nodes into a two dimensional space by using the PCA method [37, 38] to reduce the dimensionality as shown in Fig 3.

Bottom Line: As a result, knowing how collective attention distributes and flows among different websites is the first step to understand the underlying dynamics of attention on WWW.And the patterns are stable across different periods.Thus, the overall distribution and the dynamics of collective attention on websites can be well exhibited by this geometric representation.

View Article: PubMed Central - PubMed

Affiliation: Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, China; School of Systems Science, Beijing Normal University, Beijing, China.

ABSTRACT
With the fast development of Internet and WWW, "information overload" has become an overwhelming problem, and collective attention of users will play a more important role nowadays. As a result, knowing how collective attention distributes and flows among different websites is the first step to understand the underlying dynamics of attention on WWW. In this paper, we propose a method to embed a large number of web sites into a high dimensional Euclidean space according to the novel concept of flow distance, which both considers connection topology between sites and collective click behaviors of users. With this geometric representation, we visualize the attention flow in the data set of Indiana university clickstream over one day. It turns out that all the websites can be embedded into a 20 dimensional ball, in which, close sites are always visited by users sequentially. The distributions of websites, attention flows, and dissipations can be divided into three spherical crowns (core, interim, and periphery). 20% popular sites (Google.com, Myspace.com, Facebook.com, etc.) attracting 75% attention flows with only 55% dissipations (log off users) locate in the central layer with the radius 4.1. While 60% sites attracting only about 22% traffics with almost 38% dissipations locate in the middle area with radius between 4.1 and 6.3. Other 20% sites are far from the central area. All the cumulative distributions of variables can be well fitted by "S"-shaped curves. And the patterns are stable across different periods. Thus, the overall distribution and the dynamics of collective attention on websites can be well exhibited by this geometric representation.

No MeSH data available.