本文選題：微博輿情　切入點：微博預測　出處：《小型微型計算機系統(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.以新浪微博為研究對象,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測算法.首先,對微博的原始特征進行分析,從中提取關(guān)鍵特征.其次,利用信息增益算法,根據(jù)微博的傳播特征對微博的熱度進行度量.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,預測微博的傳播特征,并由此推算微博的熱度來預測該微博能否成為熱門微博.實驗表明,該算法的查準率可以達到75%以上,F1度量值保持在78%左右,能夠?qū)偘l(fā)布的微博進行熱度預測,適用于微博營銷和輿情引導等領(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】： 鄭州大學信息工程學院;
【基金】：鄭州大學新媒體公共傳播學科招標課題階段性成果項目(XMTGGCBJSZ05)資助 河南省科技攻關(guān)項目(142102310531)資助 鄭州市科技攻關(guān)計劃項目(141PPTGG368)資助
【分類號】：TP393.092;TP391.1;TP183

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本文編號：1563876