information diffusion: model, data, and...
TRANSCRIPT
Information Diffusion: Model, Data, and Prediction
Alibaba Research Center for Complexity SciencesHangzhou Normal University
Zi-Ke Zhang [email protected]
Collaborators: Chuang Liu, Xiu-Xiu Zhan, Gui-Quan Sun, Zhen Jin, Jonathan Jianhua Zhu
Outline
•Introduction
• Information Spreading
•Data-driven analysis and prediction
•Conclusions
An Open Question
• Can SI-based dynamics fully describe information spreading?
Related References• PRL 86 (2001) 3200;
• Nature 457 (2009) 1012;
• Nature Physics 6, 888 (2010);
• PRL 109 (2012) 068702;
• Science 337 (2012) 337;
• Nature Communications 5 (2013) 4323;
• Science 342 (2013 ) 1337;
• ACM Trans. Knowl. Data Eng. 9 (2015) 25.
• Review of Modern Physics 87 (2015) 925;
• Physics Reports. 651 (2016) 1;
• Physics Reports. 660 (2016) 1;
• Science 359 (2018) 1146–1151;
……
Begin with epidemics
Blind Areas(1/2)
Zhang et al, 2014
Blind Areas(2/2)
Comparison with site percolation
Outline
•Introduction
• Information Spreading
• Data-driven analysis and prediction
•Conclusions
Data of two dynamics
Both dynamics show high correlations.
Disease: the first outbreak is lower than the second one；
Information: the first outbreak is higher than the second one！
Zhan et al. Applied Mathematics and
Computation 332 (2018) 437–448
Model• Disease states: S,I
• Information states: aware(+), unaware(-)
• Set of individuals’ states:
• Other parameters:
FIG. 2: Flow diagram of SIS model.
IISS ,,,
0 , 1S I
1
Model analysis
• Information diffusion inhibits the spread of epidemic:
• (a) Slow down the speed.
• (b) Reduce the final infected size.
Theoretical Analysis
• A mean-field model：
Pairwise model
Model analysis
• Pairwise model is more accurate.
FIG. 4: The analysis of the spreading process of the SIS model:
SIS simulation (pink circle), SIS pairwise model (green solid line)
and Classical SIS model (blue dashed line).
Model analysis
(a) pairwise model;
(b) simulation
Model analysis
• The infection density has a power-law against time evolution at the critical point:
Figure 6: (Color online) Infection density as a function of β with the
pairwise analysis. The inset is the infection density as a function of time
with the pairwise analysis around the threshold.
Outline
•Introduction
• Information Spreading
•Data-driven analysis and prediction
•Conclusions
An Open Question
• Can SI-based dynamics fully describe information spreading?
DATA
•Microblogging systems: (i)China Sina Weibo; (ii)Twitter
• Sina Weibo: over 1,400,000 stories; 10,000,000 retweets;
2,400,000 users; and social network (followship) of 8,000,000
directed links.
•Twitter: over 2,000,000 stories; 150,000,000 retweets; 8,000,000
users; and social network (followship) of 100,000,000 directed
links.
In preparation
Predictability of the cascade
DATA :
• Motif Type (Entroy
• Timespan to form the
corresponding motif• Time retweeted by HubR
• Number of nodes
evolved within initial time
In preparation
Related publications
• Zi-Ke Zhang*, Chuang Liu, Xiu-Xiu Zhan, Xin Lu, Chu-Xu Zhang, Yi-Cheng Zhang*. Dynamics of information diffusion and its applications on complex networks. Physics Reports. 651 (2016) 1-34.
• Xiu-Xiu Zhan, Chuang Liu, Ge Zhou, Zi-Ke Zhang*, Gui-Quan Sun, Jonathan J. H. Zhu. Zhen Jin. Coupling dynamics of epidemic spreading and information diffusion on complex networks. Applied Mathematics and Computation 332 (2018) 437–448
• Jiao Wu, Muhua Zheng*, Zi-Ke Zhang, Wei Wang, Changgui Gu*, and Zonghua Liu. A model of spreading of sudden events on social networks. Chaos 28 (2018) 033113
• Xiu-Xiu Zhan, Chuang Liu*, Gui-Quan Sun, Zi-Ke Zhang*. Epidemic Dynamics On Information-Driven Adaptive Networks. Chaos, Solitons and Fractals 108 (2018) 196–204
• Chuang Liu, Zi-Ke Zhang*. Information spreading on dynamic social networks. Communications in Nonlinear Science and Numerical Simulation. 19(4)(2014)896–904.
• Chuang Liu, Xiu-Xiu Zhan, Zi-Ke Zhang*, Gui-Quan Sun, Pak Ming Hui. How Events Determine Spreading Patterns: Information Transmission via Internal and External Influences on Social Networks. New Journal of Physics. 17 (2015) 113045.
• Gui-Quan Sun, Zi-Ke Zhang,Global stability for a sheep brucellosis model with immigration. Applied Mathematics and Computation. 246 (2014) 336-345
• Xiu-Xiu Zhan, Chuang Liu*, Zi-Ke Zhang and Gui.-Quan Sun. Roles of edge weights on epidemic spreading dynamics. Physica A 456, 228-234, 2016.
• Ye Sun, Chuang Liu*, Chu-Xu Zhang and Zi-Ke Zhang*. Epidemic Spreading on Weighted Complex Networks. Physics Letters A 378 (2014) 635–640.
