本文選題：SIR模型 + 輿情傳播�。� 參考：《情報(bào)科學(xué)》2017年12期

【摘要】：【目的/意義】隨著移動(dòng)網(wǎng)絡(luò)技術(shù)的飛速發(fā)展,用戶已習(xí)慣在社交網(wǎng)絡(luò)平臺(tái)發(fā)表意見(jiàn),進(jìn)而形成所謂的網(wǎng)絡(luò)輿情。準(zhǔn)確建立輿情的傳播模型,對(duì)于輿情的引導(dǎo)和控制具有重要的幫助�！痉椒�/過(guò)程】本文基于傳統(tǒng)的SIR傳染病模型,綜合考慮用戶的心理特征行為因素,搭建新型的社交網(wǎng)絡(luò)輿情傳播動(dòng)力學(xué)模型,并選用粒子群算法,以2016年內(nèi)熱點(diǎn)的微博輿情事件為例,求解模型參數(shù)的最優(yōu)值,并進(jìn)行實(shí)驗(yàn)數(shù)據(jù)驗(yàn)證�！窘Y(jié)果/結(jié)論】結(jié)果表明:用戶的追根溯源心理、持續(xù)關(guān)注心理以及漠不關(guān)心心理等心理特征對(duì)輿情的傳播特性有重要影響,同時(shí)本文給出的模型由于考慮了用戶的心理特征行為因素,模型的準(zhǔn)確性相較傳統(tǒng)的SIR模型有明顯優(yōu)勢(shì),模型擬合曲線與真實(shí)數(shù)據(jù)曲線基本一致,并且模型擬合值與真實(shí)數(shù)據(jù)的絕對(duì)誤差值和RMSE值都較低。本文的研究對(duì)準(zhǔn)確預(yù)測(cè)輿情信息傳播趨勢(shì)以及輿情的分析和引導(dǎo)有著重要的指導(dǎo)作用。
[Abstract]:With the rapid development of mobile network technology, users have become accustomed to express their opinions on social network platform, and then form the so-called network public opinion. It is of great help to establish an accurate communication model of public opinion for the guidance and control of public opinion. [method / process] based on the traditional SIR infectious disease model, this paper comprehensively considers the psychological characteristics and behavioral factors of users. A new dynamic model of public opinion propagation in social networks is built, and the particle swarm optimization algorithm is used to solve the optimal parameters of the model by taking the Weibo public opinion events of hot spots in 2016 as an example. The results show that the psychological characteristics of the users, such as tracing back to the source, constant concern and indifference, have an important effect on the communication characteristics of public opinion. At the same time, the model given in this paper has obvious advantages over the traditional SIR model because of taking into account the factors of user's psychological characteristics and behavior, and the fitting curve of the model is basically consistent with the real data curve. And the absolute error value and RMSE value of model fitting value and real data are lower. The research in this paper plays an important guiding role in accurately predicting the trend of public opinion information dissemination and the analysis and guidance of public opinion.
【作者單位】： 江西師范大學(xué)傳播學(xué)院;
【基金】：國(guó)家社科基金項(xiàng)目(13CXW001)
【分類號(hào)】：G206;R181

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