1
APPENDIX S1
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Appendix A. Information dissemination model of cell phone
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Fig. S1 shows the information dissemination process of cell phone. P 1,phone is the probability that
4
person’s cell phone receiving the information and it is related to notified people (n’) in current step and
5
total population number Np. P2,phone reflects whether people could answer the cell phone and get the
6
information (from the n times cell phone experiments, there are nans(p) people answer the cell phone).
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P3, which is related to the degree of trust of cell phone (Cphone ) and received phone numbers (nrec(p)
8
can be obtained by computational simulation) in the time step, is the probability of information
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relievers to believers. P4,phone is felt to be the probability that people will spread information and the
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number of spread people (Nspr(p) ) is obtained from questionnaires.
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From the process shown in Fig. S1, effective information dissemination probability P phone is expressed
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in equation 11.
13
 
1
Pphone =P1,phone  P2,phone  P3,phone = 1  1 
  N p




n'
 n
n
  ans ( p )  1  1  C phone  rec ( p )
 n



(11)
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Delay time of the cell phone is calculated based on the data of 150 times cell phone experiments. It is a
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weighted average of delay times in different states including answering phone, busy line, powering off
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and hanging up.
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Appendix B. Information dissemination model of short message service
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Fig. S2 shows the information dissemination process of short message service. Among that, P1,SMS is
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the probability of person’s cell phone receiving the message in one step and it is related to number of
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spreaders (Nspr(SMS)), average spread number (nspr(SMS)) of spreaders and total population number (N SMS).
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P2,SMS is the probability which is related to delay time (t d (SMS)) and the time of cell phone received the
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message (trec(SMS)). P3,SMS, which is related to degree of trust of short message (CSMS ) and received
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message number (nrec(SMS) ) in the time step, is the probability of information relievers to believers.
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Among the all parameters, Nspr(SMS), P2,SMS and nrec(SMS) were obtained by simulation and nspr(SMS), NSMS
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and CSMS a
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From the process shown in Fig. S2, effective information dissemination probability P SMS is expressed
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in equation 12.
1
PSMS = P1,SMS ∗ P2,SMS ∗ P3,SMS = (1 − (1 −
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Nspr(SMS) ∗nspr(SMS)
1
NSMS
)
) · P2,SMS · （1 − (1 − CSMS )nrec(SMS) ）
(12)
Average delay time of short message is calculated based on the data of questionnaires.
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Appendix C. Information dissemination model of news portal
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Fig. S3 shows the information dissemination process of news portal. Here, the information is assumed
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to be broadcasted per half an hour. Among the process, P 1,np is the ratio of visiting news portal in the
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time periods. P2,np expresses the probability of a news portal visitor get the information from website.
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Believing probability P3,np is calculated through the degree of trust of news portal (Cportal ) and
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receiving times of information n ( n =
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probability Pnp is calculated by equation 13.
Pnp  P1,np  P2,np  P3,np
Tuse (i)
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). In summary, effective information dissemination
 Tuse (i ) Tuse (i )
n
 30  30  (1  (1  C portal ) ) ti  60 min

Tuse (i )

 (1  (1  C portal ) n )
ti  60 min

180
(13)
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Delay time of information dissemination in news portal is similar with television, and the final value is
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calculated below:
t2
t1 t2

2 2
24
0.5 
t2
2
t2
dt
 t )(
) (14)
t1 t2
2
0.5  
2 2
T1,np (t1 , t2 )  P1,np  f1, np (t )  p1, np (dt ) 
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Where T1,np is total delay time of news portal; 𝑃1,np denotes the proportion of each period to 24
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hours; f1,np (t) is the function of delay time; p1,np (dt) represents the time weight of dt.
t1
Tportal 
t
1.5 1
2
(0.75 
1  48  t (n  1) t (n)

 t t

 0.5    1  48  0.5 
 i 2 
48 
2
 2
 2 2

2
43

4.5
40
2
2



(15)