What is Market Talking About? Market-Oriented Prospect Analysis for Entrepreneur Fundraising

In recent decades, innovation and entrepreneurship have become buzz words. With entrepreneurial projects emerging in large numbers every day, the common intention of all investors, i.e., putting every penny into good entrepreneurial projects, is becoming more difficult. In reality, traditional research with empirical results is not practical for analyzing these newly launched projects of small and micro enterprises before production and sale. Actually, the future market prospect is an important criterion for evaluating entrepreneurial projects. However, this direction has not been well explored due to the limitations of scenarios and technical challenges especially for these small and micro enterprises. In this paper, we construct an interesting study of exploiting the market prospect from the sales markets (i.e., E-commerce) to help evaluate newly-posted campaigns in crowdfunding. Specifically, we propose a novel Market-oriented Prospect Analysis with Transferring Attention (MoPa-A) model which contains two learning modules, i.e., HostTask Learning and GuestTask Learning connected and enhanced by transferring attention. The former is designed for funding performance modeling with heterogeneous features of crowdfunding campaigns, and the latter is to represent and transfer the latent semantics of market prospect for target campaigns from campaigns’ comments with the help of relevant products in sales market. The model design of MoPa-A brings some new insights on flexible knowledge transfer for different or cross domains. With the real-world datasets collected from Indiegogo and Amazon, we construct extensive experiments and the results demonstrate the effectiveness of our MoPa-A model.

[1]  Enhong Chen,et al.  Estimating Fund-Raising Performance for Start-up Projects from a Market Graph Perspective , 2021, Pattern Recognit..

[2]  Chun Yuan,et al.  TranSlider: Transfer Ensemble Learning from Exploitation to Exploration , 2020, KDD.

[3]  Qi Liu,et al.  Voice of Charity: Prospecting the Donation Recurrence & Donor Retention in Crowdfunding , 2020, IEEE Transactions on Knowledge and Data Engineering.

[4]  Hui Xiong,et al.  A Comprehensive Survey on Transfer Learning , 2019, Proceedings of the IEEE.

[5]  Pengfei Wei,et al.  A General Domain Specific Feature Transfer Framework for Hybrid Domain Adaptation , 2019, IEEE Transactions on Knowledge and Data Engineering.

[6]  Jianmin Wang,et al.  Transferable Attention for Domain Adaptation , 2019, AAAI.

[7]  Enhong Chen,et al.  Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective , 2019, AAAI.

[8]  Yu Zhang,et al.  Interactive Attention Transfer Network for Cross-Domain Sentiment Classification , 2019, AAAI.

[9]  Ming Shao,et al.  Structure-Preserved Unsupervised Domain Adaptation , 2019, IEEE Transactions on Knowledge and Data Engineering.

[10]  Yue Yin,et al.  Explainable Recommendation via Multi-Task Learning in Opinionated Text Data , 2018, SIGIR.

[11]  Yu Zhang,et al.  End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification , 2017, IJCAI.

[12]  Le Wu,et al.  Tracking the Dynamics in Crowdfunding , 2017, KDD.

[13]  Qingyao Wu,et al.  Online Transfer Learning with Multiple Homogeneous or Heterogeneous Sources , 2017, IEEE Transactions on Knowledge and Data Engineering.

[14]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[15]  Hui Xiong,et al.  A Unified Framework for Metric Transfer Learning , 2017, IEEE Transactions on Knowledge and Data Engineering.

[16]  Anindya Ghose,et al.  Secret Admirers: An Empirical Examination of Information Hiding and Contribution Dynamics in Online Crowdfunding , 2016, Inf. Syst. Res..

[17]  A. Gupta,et al.  Cross-Stitch Networks for Multi-task Learning , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[18]  Yan Li,et al.  Project Success Prediction in Crowdfunding Environments , 2016, WSDM.

[19]  Chengqi Zhang,et al.  TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs , 2015, IEEE Transactions on Knowledge and Data Engineering.

[20]  Michael I. Jordan,et al.  Learning Transferable Features with Deep Adaptation Networks , 2015, ICML.

[21]  M. Puri,et al.  Adverse Incentives in Crowdfunding , 2014, Manag. Sci..

[22]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[23]  Victor S. Lempitsky,et al.  Unsupervised Domain Adaptation by Backpropagation , 2014, ICML.

[24]  Yoon Kim,et al.  Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.

[25]  Cícero Nogueira dos Santos,et al.  Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts , 2014, COLING.

[26]  Philip S. Yu,et al.  Adaptation Regularization: A General Framework for Transfer Learning , 2014, IEEE Transactions on Knowledge and Data Engineering.

[27]  Philip S. Yu,et al.  Inferring the impacts of social media on crowdfunding , 2014, WSDM.

[28]  Danushka Bollegala,et al.  Cross-Domain Sentiment Classification Using a Sentiment Sensitive Thesaurus , 2013, IEEE Transactions on Knowledge and Data Engineering.

[29]  Paul Belleflamme,et al.  Crowdfunding: Tapping the Right Crowd , 2013, SSRN Electronic Journal.

[30]  Jianmin Wang,et al.  Transfer Learning with Graph Co-Regularization , 2012, IEEE Transactions on Knowledge and Data Engineering.

[31]  O. Sorenson,et al.  Venture Capital, Entrepreneurship, and Economic Growth , 2009, The Review of Economics and Statistics.

[32]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[33]  D. D’Adda,et al.  Venture capital investments and patenting activity of high-tech start-ups: a micro-econometric firm-level analysis , 2010 .

[34]  Hans Landström,et al.  Handbook of Research on Venture Capital , 2009 .

[35]  Dietmar Harhoff,et al.  To Be Financed or Not - The Role of Patents for Venture Capital Financing , 2009 .

[36]  David H. Hsu,et al.  PATENTS AS QUALITY SIGNALS FOR ENTREPRENEURIAL VENTURES. , 2008 .

[37]  Panagiotis G. Ipeirotis,et al.  Show me the money!: deriving the pricing power of product features by mining consumer reviews , 2007, KDD '07.

[38]  David H. Hsu Experienced entrepreneurial founders, organizational capital, and venture capital funding , 2007 .

[39]  Scott Shane,et al.  Does experience matter? The effect of founding team experience on the survival and sales of newly founded ventures , 2006 .

[40]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[41]  K. Becker,et al.  Analysis of microarray data using Z score transformation. , 2003, The Journal of molecular diagnostics : JMD.

[42]  Scott Shane,et al.  Network Ties, Reputation, and the Financing of New Ventures , 2002, Manag. Sci..

[43]  Massimiliano Pontil,et al.  Support Vector Machines: Theory and Applications , 2001, Machine Learning and Its Applications.

[44]  Paul A. Gompers,et al.  The Venture Capital Revolution , 2001 .

[45]  B. Zider,et al.  How venture capital works. , 1998, Harvard business review.

[46]  Leslie A. Jeng,et al.  The Determinants of Venture Capital Funding: Evidence Across Countries , 1998 .

[47]  R. Gilson,et al.  Venture Capital and the Structure of Capital Markets: Banks Versus Stock Markets , 1997 .

[48]  Paul A. Gompers Optimal Investment, Monitoring, and the Staging of Venture Capital , 1995 .

[49]  Vance H. Fried,et al.  Toward a Model of Venture Capital Investment Decision Making , 1994 .

[50]  Shun-ichi Amari,et al.  Backpropagation and stochastic gradient descent method , 1993, Neurocomputing.

[51]  W. A. Sahlman,et al.  The structure and governance of venture-capital organizations , 1990 .

[52]  Chaffai Tekfi,et al.  Readability Formulas: an Overview , 1987, J. Documentation.

[53]  Rui Ye,et al.  Implementing transfer learning across different datasets for time series forecasting , 2021, Pattern Recognit..

[54]  Jun Zhao,et al.  Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism , 2018, EMNLP.

[55]  Kristin L. Sainani,et al.  Logistic Regression , 2014, PM & R : the journal of injury, function, and rehabilitation.

[56]  Ethan Mollick The Dynamics of Crowdfunding: An Exploratory Study , 2014 .

[57]  A. J. Visser,et al.  Innovation in entrepreneurship , 2013 .

[58]  Charles W. Hofer,et al.  Venture capitalists' decision criteria in new venture evaluation , 1993 .

[59]  Robert Hecht-Nielsen,et al.  Theory of the backpropagation neural network , 1989, International 1989 Joint Conference on Neural Networks.

[60]  Una Mansfield,et al.  Innovation and Entrepreneurship , 1986 .