Modeling Dynamic Competition on Crowdfunding Markets
Modeling Dynamic Competition on Crowdfunding Markets
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DOI：
10.1145/3178876.3186170
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发表时间：
2018-04
期刊：
影响因子：
--
通讯作者：
Yusan Lin;Peifeng Yin;Wang-Chien Lee
中科院分区：
文献类型：
--
作者：
Yusan Lin;Peifeng Yin;Wang-Chien Lee
众筹市场上通常激烈的竞争会显著影响项目的成功。虽然在预测众筹项目的成功时考虑了各种因素，但据作者所知，竞争现象尚未被调查。本文通过数据分析研究了众筹市场的竞争情况，提出了一种概率生成模型--动态市场竞争模型（DMC），用于捕捉众筹项目的竞争力。通过使用过去众筹项目的认捐历史进行实证评估，我们的方法显示出很好地捕捉项目的竞争力，并且在预测众筹项目的每日募集资金方面显著优于几种基线方法，将误差降低了31.73%至45.14%。此外，我们对项目竞争力，项目设计因素和项目成功之间的相关性的分析表明，高竞争力的项目，而在各种设置的项目设计因素的赢家，特别是令人印象深刻的高承诺目标和高价格奖励，相比，中等和低竞争力的项目。最后，由DMC学习的项目竞争力是非常有用的应用程序中预测的最终成功和天数达到认捐目标，达到85%的准确率和误差小于7天，分别与有限的信息在早期认捐阶段。
The often fierce competition on crowdfunding markets can significantly affect project success. While various factors have been considered in predicting the success of crowdfunding projects, to the best knowledge of the authors, the phenomenon of competition has not been investigated. In this paper, we study the competition on crowdfunding markets through data analysis, and propose a probabilistic generative model, Dynamic Market Competition (DMC) model, to capture the competitiveness of projects in crowdfunding. Through an empirical evaluation using the pledging history of past crowdfunding projects, our approach has shown to capture the competitiveness of projects very well, and significantly outperforms several baseline approaches in predicting the daily collected funds of crowdfunding projects, reducing errors by 31.73% to 45.14%. In addition, our analyses on the correlations between project competitiveness, project design factors, and project success indicate that highly competitive projects, while being winners under various setting of project design factors, are particularly impressive with high pledging goals and high price rewards, comparing to medium and low competitive projects. Finally, the competitiveness of projects learned by DMC is shown to be very useful in applications of predicting final success and days taken to hit pledging goal, reaching 85% accuracy and error of less than 7 days, respectively, with limited information at early pledging stage.