CAJ | 학술논문

转发行为是微博平台上信息传播的主要形式。目前已有的工作大多数聚焦在转发行为的分析和预测。针对给定的一条微博时如何找到其转发者这个问题并没有得到很好的解决。结合贝叶斯个性化排序优化标准（BPR-OPT）和分解机（FM），提出了一种通用的方法用于对微博转发者进行预测，并进一步对影响用户成为转发者的特征因素进行了细致分析，然后根据这些特征，在大规模真实数据集上对微博转发者进行了预测。实验证明该方法能够明显提高预测效果，同时也验证了基于pair-wise和特征相关的方法能更有效解决微博转发者预测问题。
전발행위시미박평태상신식전파적주요형식。목전이유적공작대다수취초재전발행위적분석화예측。침대급정적일조미박시여하조도기전발자저개문제병몰유득도흔호적해결。결합패협사개성화배서우화표준（BPR-OPT）화분해궤（FM），제출료일충통용적방법용우대미박전발자진행예측，병진일보대영향용호성위전발자적특정인소진행료세치분석，연후근거저사특정，재대규모진실수거집상대미박전발자진행료예측。실험증명해방법능구명현제고예측효과，동시야험증료기우pair-wise화특정상관적방법능경유효해결미박전발자예측문제。
The repost action is the main way for information spreading in Micro-blogging platform.Nowadays,many works have been done focusing on the repost behaviorsanalysis and prediction.However,the problem about how to find the users who are the most likely to repost a given Micro-blog remains unsolved.In this paper,a general predictor, which combines Bayesian Personalized Ranking optimization criterion with Factorization Machines was presented to pre-dict the reposter of a microblog.Furthermore,factors which affect a user to be a reposter were analyzed in details.With these facts,prediction of the reposters over large-scale real datasets was conducted.The experiment proves that this method can improve the effect of the prediction obviously.Meanwhile,method based on pair-wise and feature-related can solve the prediction problem more efficiently.