论文标题
这全都在（子）标题中吗？在众筹研究中扩大信号评估
It's all in the (Sub-)title? Expanding Signal Evaluation in Crowdfunding Research
论文作者
论文摘要
关于众筹成功的研究（计算机辅助文本分析）正在迅速发展到大联盟（例如，Parhankangas和Renko，2017; Anglin等，2018; Moss等，2018，通常是基于信息的信息，社会资本，信号，信号或组合。但是，探索众筹成功标准的当前论文无法利用可用的全部信号，只有很少的此类论文研究技术项目。在本文中，我们将企业家的文本成功信号的强度与该类别的支持者进行比较和对比。基于从Kickstarter收集的1,049个技术项目的随机样本，我们不仅从项目标题和描述中评估文本信息，而且从视频字幕中评估。我们发现，合并字幕信息增加了各自模型所解释的差异，从而增加了其资金成功的预测能力。通过扩大信息格局，我们的工作为该领域提供了进步，并为对众筹成功信号进行了更细粒度的研究铺平了道路，因此可以提高对人群中投资者决策的了解。
Research on crowdfunding success that incorporates CATA (computer-aided text analysis) is quickly advancing to the big leagues (e.g., Parhankangas and Renko, 2017; Anglin et al., 2018; Moss et al., 2018) and is often theoretically based on information asymmetry, social capital, signaling or a combination thereof. Yet, current papers that explore crowdfunding success criteria fail to take advantage of the full breadth of signals available and only very few such papers examine technology projects. In this paper, we compare and contrast the strength of the entrepreneur's textual success signals to project backers within this category. Based on a random sample of 1,049 technology projects collected from Kickstarter, we evaluate textual information not only from project titles and descriptions but also from video subtitles. We find that incorporating subtitle information increases the variance explained by the respective models and therefore their predictive capability for funding success. By expanding the information landscape, our work advances the field and paves the way for more fine-grained studies of success signals in crowdfunding and therefore for an improved understanding of investor decision-making in the crowd.
