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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 normalized cumulative curves of attention flows (brown diamond), attention dissipations (blue squares), and the number of websites (green circles) along radius.The fitted normalized “S” curves for attention flows (dotted brown), dissipations (dashed and dotted blue), and the number of sites (dashed dark lines) are also shown. The inset shows the density curves of the three quantities and the derivatives to R of the three fitted “S” curves.
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pone.0136243.g005: The normalized cumulative curves of attention flows (brown diamond), attention dissipations (blue squares), and the number of websites (green circles) along radius.The fitted normalized “S” curves for attention flows (dotted brown), dissipations (dashed and dotted blue), and the number of sites (dashed dark lines) are also shown. The inset shows the density curves of the three quantities and the derivatives to R of the three fitted “S” curves.

Mentions: Because Google.com has the smallest average distance to other websites, it is set as the center of the geometric representation for all other websites which form a nearly symmetric ball around the center. Therefore, we study the distributions of the variables including attention flow (the traffic of each web site), attention dissipation (the flow to the sink from each web site), and the number of websites along the distance from the center of the ball. Instead of drawing the density curves of focal quantities directly, we accumulate them within the given radius to reduce the effect of noise in the data because cumulative curves are equivalent to density curves for distributions. We discover that with the increase of radius, the cumulative amounts of the quantities within the radius show sigmoid growth patterns (see Fig 5) and this S-curve pattern is very stable for different periods, namely October 10,2006, March 10,2007, September 10,2007 and February 10,2008. Details are shown in the supporting information.


A Geometric Representation of Collective Attention Flows.

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

The normalized cumulative curves of attention flows (brown diamond), attention dissipations (blue squares), and the number of websites (green circles) along radius.The fitted normalized “S” curves for attention flows (dotted brown), dissipations (dashed and dotted blue), and the number of sites (dashed dark lines) are also shown. The inset shows the density curves of the three quantities and the derivatives to R of the three fitted “S” curves.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0136243.g005: The normalized cumulative curves of attention flows (brown diamond), attention dissipations (blue squares), and the number of websites (green circles) along radius.The fitted normalized “S” curves for attention flows (dotted brown), dissipations (dashed and dotted blue), and the number of sites (dashed dark lines) are also shown. The inset shows the density curves of the three quantities and the derivatives to R of the three fitted “S” curves.
Mentions: Because Google.com has the smallest average distance to other websites, it is set as the center of the geometric representation for all other websites which form a nearly symmetric ball around the center. Therefore, we study the distributions of the variables including attention flow (the traffic of each web site), attention dissipation (the flow to the sink from each web site), and the number of websites along the distance from the center of the ball. Instead of drawing the density curves of focal quantities directly, we accumulate them within the given radius to reduce the effect of noise in the data because cumulative curves are equivalent to density curves for distributions. We discover that with the increase of radius, the cumulative amounts of the quantities within the radius show sigmoid growth patterns (see Fig 5) and this S-curve pattern is very stable for different periods, namely October 10,2006, March 10,2007, September 10,2007 and February 10,2008. Details are shown in the supporting information.

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.