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基于多特征的熱門微博預(yù)測算法研究

發(fā)布時(shí)間:2018-03-04 03:13

  本文選題:微博輿情 切入點(diǎn):微博預(yù)測 出處:《小型微型計(jì)算機(jī)系統(tǒng)》2017年03期  論文類型:期刊論文


【摘要】:隨著微博的迅猛發(fā)展,微博輿情已經(jīng)成為研究熱點(diǎn).以新浪微博為研究對(duì)象,分析熱門微博的影響因素,提出一種基于多特征的熱門微博預(yù)測算法.首先,對(duì)微博的原始特征進(jìn)行分析,從中提取關(guān)鍵特征.其次,利用信息增益算法,根據(jù)微博的傳播特征對(duì)微博的熱度進(jìn)行度量.最后,結(jié)合BP神經(jīng)網(wǎng)絡(luò)算法,根據(jù)微博的內(nèi)容和博主特征,預(yù)測微博的傳播特征,并由此推算微博的熱度來預(yù)測該微博能否成為熱門微博.實(shí)驗(yàn)表明,該算法的查準(zhǔn)率可以達(dá)到75%以上,F1度量值保持在78%左右,能夠?qū)偘l(fā)布的微博進(jìn)行熱度預(yù)測,適用于微博營銷和輿情引導(dǎo)等領(lǐng)域.
[Abstract]:With the rapid development of Weibo, Weibo public opinion has become a hot research topic. Based on the analysis of influential factors of popular Weibo, this paper proposes a multi-feature based prediction algorithm for popular Weibo. First of all, This paper analyzes Weibo's original features and extracts the key features from them. Secondly, the heat intensity of Weibo is measured by using the information gain algorithm, according to the propagating characteristics of Weibo. Finally, the BP neural network algorithm is combined with the BP neural network algorithm. Based on Weibo's content and blogger's characteristics, we can predict the transmission characteristics of Weibo, and then calculate the heat of Weibo in order to predict whether it will become a hot Weibo. The experiment shows that, The precision of the algorithm can reach 75% or more and the F1 measure can be kept around 78%. It can predict the heat of Weibo which has just been published and can be used in the field of Weibo marketing and public opinion guidance.
【作者單位】: 鄭州大學(xué)信息工程學(xué)院;
【基金】:鄭州大學(xué)新媒體公共傳播學(xué)科招標(biāo)課題階段性成果項(xiàng)目(XMTGGCBJSZ05)資助 河南省科技攻關(guān)項(xiàng)目(142102310531)資助 鄭州市科技攻關(guān)計(jì)劃項(xiàng)目(141PPTGG368)資助
【分類號(hào)】:TP393.092;TP391.1;TP183

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

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本文編號(hào):1563876


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