Detecting Fraudulent Behavior on Crowdfunding Platforms: The Role of Linguistic and Content-Based Cues in Static and Dynamic Contexts

Abstract

Crowdfunding platforms offer founders the possibility to collect funding for project realization. With the advent of these platforms, the risk of fraud has risen. Fraudulent founders provide inaccurate information or pretend interest toward a project. Within this study, we propose deception detection support mechanisms to address this novel type of Internet fraud. We analyze a sample of fraudulent and nonfraudulent projects published at a leading crowdfunding platform. We examine whether the analysis of dynamic communication during the funding period is valuable for identifying fraudulent behavior—apart from analyzing only the static information related to the project. We investigate whether content-based cues and linguistic cues are valuable for fraud detection. The selection of cues and the subsequent feature engineering is based on theories in areas of communication, psychology, and computational linguistics. Our results should be helpful to the stakeholders of crowdfunding platforms and researchers of fraud detection.

Key words and phrases:

• crowdfunding
• deception detection
• fraud detection
• text mining
• content-based cues
• linguistic cues

Notes

1. www.kickstarter.com/help/stats (accessed on September 25, 2015).

Additional information

Notes on contributors

Michael Siering

Michael Siering ([email protected]) is a Postdoctoral Research Associate at Goethe University Frankfurt, Germany, and a Research Associate at the E-Finance Lab, an industry-academic partnership between that university and several industry partners. He holds a Ph.D. in business administration from Goethe University Frankfurt. His research focuses on decision support systems in electronic markets, with a concentration on the analysis of user-generated content by means of sentiment analysis and text mining. His work has been published in Decision Support Systems and the conference proceedings of ICIS, ECIS, and HICSS.

Jascha-Alexander Koch

Jascha-Alexander Koch ([email protected]) is a doctoral candidate at Goethe University Frankfurt and a Research Assistant at the E-Finance Lab. He holds an M.Sc. in business administration and electrical engineering from the University of Brunswick. He engages in research on crowdfunding, and focuses especially on crowdfunding platforms, platform participants, and the conduction of crowdfunding campaigns. His work has been published in the Conference Proceedings of ECIS and PACIS.

Amit V. Deokar

Amit V. Deokar ([email protected]; corresponding author) is an Assistant Professor of Management Information Systems in the Robert J. Manning School of Business at the University of Massachusetts Lowell. He received his Ph.D. in management information systems from the University of Arizona. His research interests include predictive analytics, business intelligence, process management, and collaboration processes and technologies. His work has been published in the Journal of Management Information Systems, Decision Support Systems (DSS), IEEE Transactions, and others. He is currently a member of the editorial board of DSS. He was recognized with the 2014 IBM Faculty Award for his research and teaching in the areas of analytics and big data.