Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020 Success Factors of Donation-Based Crowdfunding Campaigns: A Machine Learning Approach Massara Alazazi Bin Wang Tareq Allan University of Texas University of Texas Dakota State University Rio Grande Valley Rio Grande Valley [email protected] [email protected] [email protected] Abstract when compared with traditional forms of funding [1]. While crowdfunding is a relatively new phenomena, Crowdfunding has emerged as an alternative it has gained popularity, since lack of financial mechanism to traditional financing mechanisms in resources and limited access to them are identified as which individuals solicit financial capital or donation key problems for the operation of small and medium- from the crowd. The success factors of crowdfunding sized enterprises [4]. are not well-understood, particularly for donation- Crowdfunding platforms support millions of based crowdfunding platforms. This study identifies crowdfunding campaigns from various categories and key drivers of donation-based crowdfunding for different purposes. Although some campaigns campaign success using a machine learning would have similar goals or projects, their success approach. Based on an analysis of crowdfunding rate may vary. Successful campaigns attract the campaigns from Gofundme.com, we show that our crowd and persuade people about their goals and models were able to predict the average daily amount motives for the campaign. Furthermore, the ability to received at a high level of accuracy using variables propagate those campaigns to other people through available at the beginning of the campaign and the social media increases the social media buzz for the number of days it had been posted. In addition, fundraising and thus increases its ability to succeed Facebook and Twitter shares and the number of likes, [5]. improved the accuracy of the models. Among the six Despite the growing popularity of crowdfunding, machine learning algorithms we used, support vector there is a need to better understand this relatively new machine (SVM) performs the best in predicting social phenomena [6]. Although many people turn to campaign success. crowdfunding to support their projects financially, not all projects get the funds they aim for. For instance, only 44% of all projects on Kickstarter 1. Introduction reached their goal [7]. Hence, there is a need to understand this funding variation. There is also a lack Many individuals turn to the social media to of understanding of the dynamics of successful solicit financial help from the general public, which crowdfunding [3]. Crowdfunding platforms provide is called the “crowd”, rather than the traditional categories of campaigns according to their purpose financial fund seeking including business angels or and description. These categories include emergency, venture capital funds [1].This activity is called medical, art, sports, nonprofit, and others. Variations crowdfunding, which is a form of crowdsourcing that of crowdfunding activities between different is facilitated by the Web 2.0 technologies. It not only categories are not well studied. opens the doors for people from all over the world to In addition, most existing studies focus on reach others and communicate, but also enables them reward-based crowdfunding platforms such as to support others financially [2]. Crowdfunding is an Kickstarter [3, 8]. In this study, we employ data from open call funding mechanism that depends on small a donation-based crowdfunding platform, since there portions of funds from a relatively large number of are few studies that examine this type of people through online platforms for the purpose of crowdfunding business model and funding activities. financing a venture or project investment, without Our study applies a machine learning approach, standard financial intermediaries [3]. Crowdfunding which is rarely in crowdfunding research. Thus, our enables fundraisers to get financial support for their research purpose is to: future ventures at a considerably low cost and risk URI: https://hdl.handle.net/10125/64048 978-0-9981331-3-3 Page 2507 (CC BY-NC-ND 4.0) 1. Identify key drivers of donation-based crowdfunding allows more efficient investment crowdfunding campaign success. decisions. It facilitates interactions between project 2. Compare the performance of different creators and funders, who could be future consumers, machine learning algorithms and the eliminating geographic barriers [17]. regression model approach in predicting donation-based crowdfunding campaign Previous research studied the motivation factors success. to fund crowdfunding campaigns include connecting In the remainder of the paper, we first discuss the with others, learning, collecting funds for different related literature on crowdfunding as a social projects, and distributing awareness regarding financial phenomenon. Next, we discuss the machine different issues [6]. The study applies a grounded learning approach and compare different algorithms, theory method through semi-structured interviews. followed by the empirical study including the data, Another study explored the dynamics of analysis, and results. Finally, the paper discusses the crowdfunding [3]. It collected data from Kickstarter results and future research directions. and found that Personal networks, project quality, and geography are associated with the success of 2. Literature Review crowdfunding efforts. Furthermore, a previous study focused on the drivers of crowdfunding success from IndieGoGo funding campaigns [18]. The study 2.1 Crowdsourcing and Crowdfunding identified eight campaign success drivers including Phenomena image, cause of need, picture appeal, perspective advocated, social comparisons, decisional control, The crowdsourcing phenomena flourished with labeling and request sizes. In addition, funding goal the diffusion of information and telecommunications and the number of comments affect campaign technologies, particularly the social media [9]. success. Other research discussed more specific Crowdsourcing has been applied in many areas factors such as the emotional delivery impact on pro- including crowdsourcing to obtain product social crowdfunding success. The study uses image specifications or improvement, crowdsourcing for classification software to analyze facial expressions answering academic problems, crowdsourcing for in photos attached to the campaign. The study driving accident reporting, and crowdsourcing for concluded that fundraisers use emotions to solicit innovative business ideas [10]. Accordingly, many money and attract funders, since there are usually no applications and online platforms are founded financial incentives for funders to support these including Amazon’s Mechanical Turk and Dell campaigns. Emotions and visual expressions are key IdeaStorm [10]. Incentives (e.g., rewards, feedback, factors in affecting the success of the campaigns [19]. and rivalry) in crowdsourcing have been studied by In addition, a previous study explored how physical some researchers [11-14]. distance would impact the fundraising effort through They found that rewards, positive feedback, and analyzing data extracted from Sellaband platform rivalry motivate individuals to provide their input and campaigns on artist-entrepreneurs with related participate. The wisdom of the crowd, in which a geographic information on backers from Google large number of solvers contribute to a successful maps. The study found that funding is not solution, promotes the application of crowdsourcing geographically constrained. However, geographic by many organizations and individuals [15]. distance played a role in financing musical projects. Crowdfunding is a form of crowdsourcing, and it This impact is apparent for investors who have has been defined by Mollick [3] as “the efforts by personal connections with the artist-entrepreneur [8]. entrepreneurial individuals and groups – cultural, Other research efforts focused on crowdfunding social, and for-profit – to fund their ventures by from different perspectives. For instance, a previous drawing on relatively small contributions from a study investigates crowdfunding from the economic relatively large number of individuals using the perspective. Particularly, it looks at transaction costs, Internet, without standard financial intermediaries.” reputation, and market design and their impacts on Crowdfunding is divided into four types depending the rise of non-equity crowdfunding. It collected data on the return to the funders: reward-based, equity- from Kickstarter to identify crowdfunding platform based, loan-based, and donation-based [16]. rules to maximize transaction volume [16]. In Crowdfunding is used as an alternative source of addition, focusing on the medical crowdfunding small and medium-sized enterprise financing through campaigns for organ transplantation behavior, a study the Internet to leverage large audience contributions by Durand et al. [20] found, after applying bivariate [1]. In addition to the financial benefits, and multivariate analyses, that more positive Page 2508 sentiment, lengthier campaign description, higher the output variable in order to learn the mapping goal amount, and third person description positively function from the input to the output variable. affect the amount of fund raised by the campaign. As Because machine learning does not require “rigid” can be seen from these studies, the results are statistical assumptions,