Emotional Intensity-based Success Prediction Model for Crowdfunded Campaigns

作者：

Highlights：

• intensity of emotions mined from textual descriptions of crowdfunding campaigns are effective features to predict their success

• pre-trained word embeddings can be used to create interpretable predictive models for crowdfunding campaigns success forecasting

• predictive models interpretability opens to causal inference analysis and enables interdisciplinary studies

摘要

•intensity of emotions mined from textual descriptions of crowdfunding campaigns are effective features to predict their success•pre-trained word embeddings can be used to create interpretable predictive models for crowdfunding campaigns success forecasting•predictive models interpretability opens to causal inference analysis and enables interdisciplinary studies

论文关键词：Domain aspect mining,Aspect-based sentiment analysis,SenticNet,Interpretability,Kickstarter,Crowdfunding campaign success prediction

论文评审过程：Received 25 January 2020, Revised 24 August 2020, Accepted 18 September 2020, Available online 29 September 2020, Version of Record 29 September 2020.

论文官网地址：https://doi.org/10.1016/j.ipm.2020.102394