上海理工大学学报
上海理工大學學報
상해리공대학학보
2014年
4期
345-350
,共6页
谣言传播模型%均匀网络%无标度网络%传播率函数%移出率函数
謠言傳播模型%均勻網絡%無標度網絡%傳播率函數%移齣率函數
요언전파모형%균균망락%무표도망락%전파솔함수%이출솔함수
rumor spreading model%homogeneous network%scale-free network%spreading ratefunction%removalratefunction
经典的谣言传播模型的研究中,谣言传播率和移出率通常被视为常数,根据实际情况提出传播率和移出率变化的谣言传播模型,在均匀网络和无标度网络中分别研究了传播率和移出率随时间变化的谣言传播模型,建立相应的平均场方程,并在Matlab中进行数值分析。结果显示在传播率和移出率变化的谣言传播模型中,传播阈值依然存在,谣言最终的影响力较传播率和移出率不变的情况更为显著。此外,通过均匀网络与无标度网络谣言传播的对比分析发现,在传播率和移出率随时间变化的情况下,网络拓扑结构对谣言传播也有很大影响,并且均匀网络中谣言最终的影响力较无标度网络中谣言的最终影响力更为显著。
經典的謠言傳播模型的研究中,謠言傳播率和移齣率通常被視為常數,根據實際情況提齣傳播率和移齣率變化的謠言傳播模型,在均勻網絡和無標度網絡中分彆研究瞭傳播率和移齣率隨時間變化的謠言傳播模型,建立相應的平均場方程,併在Matlab中進行數值分析。結果顯示在傳播率和移齣率變化的謠言傳播模型中,傳播閾值依然存在,謠言最終的影響力較傳播率和移齣率不變的情況更為顯著。此外,通過均勻網絡與無標度網絡謠言傳播的對比分析髮現,在傳播率和移齣率隨時間變化的情況下,網絡拓撲結構對謠言傳播也有很大影響,併且均勻網絡中謠言最終的影響力較無標度網絡中謠言的最終影響力更為顯著。
경전적요언전파모형적연구중,요언전파솔화이출솔통상피시위상수,근거실제정황제출전파솔화이출솔변화적요언전파모형,재균균망락화무표도망락중분별연구료전파솔화이출솔수시간변화적요언전파모형,건립상응적평균장방정,병재Matlab중진행수치분석。결과현시재전파솔화이출솔변화적요언전파모형중,전파역치의연존재,요언최종적영향력교전파솔화이출솔불변적정황경위현저。차외,통과균균망락여무표도망락요언전파적대비분석발현,재전파솔화이출솔수시간변화적정황하,망락탁복결구대요언전파야유흔대영향,병차균균망락중요언최종적영향력교무표도망락중요언적최종영향력경위현저。
In the study of classical rumor spreading models,rumor spreading rate and removal rate are generally regarded as constants.Based on practical situations,a rumor spreading function and a removal rate function were proposed and a rumor spreading model with variable spreading rate and removal rate was studied in homogeneous and scale-free networks respectively.Mean-field equations were derived and numerical simulations were conducted in Matlab.The results show that in the rumor spreading model with variable spreading rate and removal rate,spreading threshold still exists and the final size of rumor spreading is larger than that in the rumor spreading model with constant spreading rate and removal rate.Furthermore,the comparison between rumor spreading processes in homogeneous network and heterogeneous network shows that network topological structure has a great impact on rumor spreading.The final size of rumor spreading in homogeneous network is larger than that in scale-free network.