【摘要】：為了評(píng)價(jià)微博的傳播效果,在分析影響用戶轉(zhuǎn)發(fā)行為因素的基礎(chǔ)上,提出了采用用戶影響力、用戶活躍度、興趣相似度、微博內(nèi)容重要性和用戶親密程度五項(xiàng)特征進(jìn)行轉(zhuǎn)發(fā)行為預(yù)測(cè)的SVM算法,以及基于該算法的轉(zhuǎn)發(fā)規(guī)模預(yù)測(cè)算法。最后給出了傳播規(guī)模預(yù)測(cè)的評(píng)價(jià)方法。針對(duì)新浪微博用戶數(shù)據(jù)的實(shí)驗(yàn)表明,預(yù)測(cè)精度達(dá)到了86.63%。
[Abstract]:In order to evaluate the transmission effect of Weibo, on the basis of analyzing the factors that affect the user's forwarding behavior, the author proposes to adopt user influence, user activity, interest similarity, etc. The SVM algorithm for predicting forwarding behavior based on the five features of Weibo's content importance and user's closeness, as well as the algorithm for predicting forwarding scale based on this algorithm. Finally, the evaluation method of propagation scale prediction is given. For Sina Weibo user data experiments show that the accuracy of the prediction reached 86.63.
【作者單位】： 國(guó)家數(shù)字交換系統(tǒng)工程技術(shù)研究中心;
【基金】：國(guó)家“863”計(jì)劃資助項(xiàng)目(2011AA010603)
【分類號(hào)】：TP393.092

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