The Atlas of Chinese World Wide Web Ecosystem Shaped by the Collective Attention Flows.
The web can be regarded as an ecosystem of digital resources connected and shaped by collective successive behaviors of users. Knowing how people allocate limited attention on different resources is of great importance. To answer this, we embed the most popular Chinese web sites into a high dimensional Euclidean space based on the open flow network model of a large number of Chinese users' collective attention flows, which both considers the connection topology of hyperlinks between the sites and the collective behaviors of the users. With these tools, we rank the web sites and compare their centralities based on flow distances with other metrics. We also study the patterns of attention flow allocation, and find that a large number of web sites concentrate on the central area of the embedding space, and only a small fraction of web sites disperse in the periphery. The entire embedding space can be separated into 3 regions(core, interim, and periphery). The sites in the core (1%) occupy a majority of the attention flows (40%), and the sites (34%) in the interim attract 40%, whereas other sites (65%) only take 20% flows. What's more, we clustered the web sites into 4 groups according to their positions in the space, and found that similar web sites in contents and topics are grouped together. In short, by incorporating the open flow network model, we can clearly see how collective attention allocates and flows on different web sites, and how web sites connected each other.
School of Systems Science, Beijing Normal University, Beijing, China.
Xiaodan
X
Lou
College of Computer Science and Engineering, Northwest Normal University, LanZhou, China.
Yong
Y
Li
School of Systems Science, Beijing Normal University, Beijing, China.
Weiwei
W
Gu
School of Systems Science, Beijing Normal University, Beijing, China.
Jiang
J
Zhang
D000465:Algorithms; D001288:Attention; D002681:China; D006801:Humans; D020407:Internet / Q000706:statistics & numerical data*