北京大学信息科学技术学院,北京,100871
网络首发:2017-04-10,
纸质出版:2017
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杨扬 1, Chun-Ta LU 2, 王菲菲 3, 等. 众筹项目的社交网络影响力预测与分析[J]. 西安交通大学学报, 2017,51(4):91-96.
Prediction and Analysis of Social Influence for Crowdfunding Projects[J]. 2017, 51(4): 91-96.
杨扬 1, Chun-Ta LU 2, 王菲菲 3, 等. 众筹项目的社交网络影响力预测与分析[J]. 西安交通大学学报, 2017,51(4):91-96. DOI: 10.7652/xjtuxb201704014.
Prediction and Analysis of Social Influence for Crowdfunding Projects[J]. 2017, 51(4): 91-96. DOI: 10.7652/xjtuxb201704014.
针对众筹项目由于社会影响力不足而成功率较低的问题
提出了面向众筹平台的社交网络影响力预测方法。该方法基于众筹网站和社交网络的实时观测数据
分别提取累积和增量等多类别预测特征
并随着社会推广的进行而渐进地预测项目的社交网络影响力增益
最后采用带L1一范数约束惩罚的逻辑回归等方法进行预测特征分析。实验结果表明:在整个推广过程中
众筹项目的社交网络影响力可以被精确预测
准确率最高达88.31%; 分类器在采用累积特征时具有比采用增量特征更好的预测效果; 项目统计特征和推广者的社会影响力等特征具有更高的重要性和更稳定的显著性。该方法成功地解决了众筹项目的社会影响力预测问题
并为设计更好的社交网络推广策略提供了依据。
A novel influence prediction method is proposed to deal with the social promotion problem on crowdfunding platforms and to investigate the predictability of social influence for fundraising projects. The proposed method gradually predicts future influence growth of each project based on features extracted in different timestamps from data streams of crowdfunding websites and social networks. Experimental results show that features extracted from aggregate data rather than incremental data are better indicators of the social influence growth
and the method has the highest prediction precision 88.31%. Analysis of features also shows that some features such as the statistic of projects and social influence of promoters are consistently significant within the prediction process. These results provide hints for devising better social promotions.
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