In Crowdfunding platforms, people turn their prototype ideas into real products by raising money from the crowd, or invest in someone else's projects. In reward-based crowdfunding platforms such as Kickstarter and Indiegogo, selecting accurate reward delivery duration becomes crucial for creators, backers, and platform providers to keep the trust between the creators and the backers, and the trust between the platform providers and users. According to Kickstarter, 35 backers did not receive rewards on time. Unfortunately, little is known about on-time and late reward delivery projects, and there is no prior work to estimate reward delivery duration. To fill the gap, in this paper, we (i) extract novel features that reveal latent difficulty levels of project rewards; (ii) build predictive models to identify whether a creator will deliver all rewards in a project on time or not; and (iii) build a regression model to estimate accurate reward delivery duration (i.e., how long it will take to produce and deliver all the rewards). Experimental results show that our models achieve good performance -- 82.5 accuracy, 78.1 RMSE, and 0.108 NRMSE at the first 5 of the longest reward delivery duration.
Researchers analyzed crowdfunding platforms @cite_3 @cite_8 . For example, @cite_4 showed the dynamics of Kickstarter donors. @cite_19 studied the dynamics of crowdfunding and revealed that personal networks and underlying project quality were related to the crowdfunding success. @cite_9 analyzed why people created and or backed projects in crowdfunding platforms. @cite_20 @cite_27 showed various factors to make a project successful in terms of the fundraising. Joenssen and M "u llerleile @cite_13 analyzed 42k Indiegogo projects, and discovered that scarcity management was problematic and reduced the chances of projects to successfully achieve the fundraising goal. Researchers @cite_24 @cite_6 @cite_22 studied the impact of social media and social communities in raising fund. @cite_11 showed that timing and communication were two key factors to make projects successful.
@cite_4 @cite_22 @cite_8 @cite_9 @cite_3 @cite_6 @cite_24 @cite_19 @cite_27 @cite_13 @cite_20 @cite_11
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Crowdfunding platforms have become important sites where people can create projects to seek funds toward turning their ideas into products, and back someone else's projects. As news media have reported successfully funded projects (e.g., Pebble Time, Coolest Cooler), more people have joined crowdfunding platforms and launched projects. But in spite of rapid growth of the number of users and projects, a project success rate at large has been decreasing because of launching projects without enough preparation and experience. Little is known about what reactions project creators made (e.g., giving up or making the failed projects better) when projects failed, and what types of successful projects we can find. To solve these problems, in this manuscript we (i) collect the largest datasets from Kickstarter, consisting of all project profiles, corresponding user profiles, projects' temporal data and users' social media information; (ii) analyze characteristics of successful projects, behaviors of users and understand dynamics of the crowdfunding platform; (iii) propose novel statistical approaches to predict whether a project will be successful and a range of expected pledged money of the project; (iv) develop predictive models and evaluate performance of the models; (v) analyze what reactions project creators had when project failed, and if they did not give up, how they made the failed projects successful; and (vi) cluster successful projects by their evolutional patterns of pledged money toward understanding what efforts project creators should make in order to get more pledged money. Our experimental results show that the predictive models can effectively predict project success and a range of expected pledged money. Crowdfunding platforms have become important sites where people can create projects to seek funds toward turning their ideas into products, and back someone else's projects. As news media have reported successfully funded projects (e.g., Pebble Time, Coolest Cooler), more people have joined crowdfunding platforms and launched projects. But in spite of rapid growth of the number of users and projects, a project success rate at large has been decreasing because of launching projects without enough preparation and experience. To solve the problem, in this paper we (i) collect the largest datasets from Kickstarter, consisting of all project profiles, corresponding user profiles, projects' temporal data and users' social media information; (ii) analyze characteristics of successful projects, behaviors of users and understand dynamics of the crowdfunding platform; (iii) propose novel statistical approaches to predict whether a project will be successful and a range of expected pledged money of the project; and (iv) develop predictive models and evaluate performance of the models. Our experimental results show that the predictive models can effectively predict project success and a range of expected pledged money. Crowdfunding has gained widespread attention in recent years. Despite the huge success of crowdfunding platforms, the percentage of projects that succeed in achieving their desired goal amount is only around 40 . Moreover, many of these crowdfunding platforms follow "all-or-nothing" policy which means the pledged amount is collected only if the goal is reached within a certain predefined time duration. Hence, estimating the probability of success for a project is one of the most important research challenges in the crowdfunding domain. To predict the project success, there is a need for new prediction models that can potentially combine the power of both classification (which incorporate both successful and failed projects) and regression (for estimating the time for success). In this paper, we formulate the project success prediction as a survival analysis problem and apply the censored regression approach where one can perform regression in the presence of partial information. We rigorously study the project success time distribution of crowdfunding data and show that the logistic and log-logistic distributions are a natural choice for learning from such data. We investigate various censored regression models using comprehensive data of 18K Kickstarter (a popular crowdfunding platform) projects and 116K corresponding tweets collected from Twitter. We show that the models that take complete advantage of both the successful and failed projects during the training phase will perform significantly better at predicting the success of future projects compared to the ones that only use the successful projects. We provide a rigorous evaluation on many sets of relevant features and show that adding few temporal features that are obtained at the project's early stages can dramatically improve the performance. Crowdfunding sites like Kickstarter--where entrepreneurs and artists look to the internet for funding--have quickly risen to prominence. However, we know very little about the factors driving the 'crowd' to take projects to their funding goal. In this paper we explore the factors which lead to successfully funding a crowdfunding project. We study a corpus of 45K crowdfunded projects, analyzing 9M phrases and 59 other variables commonly present on crowdfunding sites. The language used in the project has surprising predictive power accounting for 58.56 of the variance around successful funding. A closer look at the phrases shows they exhibit general persuasion principles. For example, also receive two reflects the principle of Reciprocity and is one of the top predictors of successful funding. We conclude this paper by announcing the release of the predictive phrases along with the control variables as a public dataset, hoping that our work can enable new features on crowdfunding sites--tools to help both backers and project creators make the best use of their time and money. Entrepreneurs are turning to crowdfunding as a way to finance their creative ideas. Crowdfunding involves relatively small contributions of many consumer-investors over a fixed time period (generally a few weeks). The purpose of this paper is to add to our empirical understanding of backer dynamics over the project funding cycle. Two years of publicly available data on projects listed on Kickstarter is used to establish that the typical pattern of project support is U-shaped — in general, backers are more likely to contribute to a project in the first and last week as compared to the middle period of the funding cycle. We further establish that this U-shape pattern of support is pervasive across projects, including both successfully and unsuccessfully funded projects, those with large and small goals, and projects in different categories. We then empirically explore the dynamics associated with several factors, including collective attention effects from platform sorting options, the role of family and friends in supporting projects, the effects of social influence, and the role of project updates over the project funding cycle. Crowdfunding -- in which people can raise funds through collaborative contributions of general public (i.e., crowd) -- has emerged as a billion dollars business for supporting more than one million ventures. However, very few research works have examined the process of crowdfunding. In particular, none has studied how social networks help crowdfunding projects to succeed. To gain insights into the effects of social networks in crowdfunding, we analyze the hidden connections between the fundraising results of projects on crowdfunding websites and the corresponding promotion campaigns in social media. Our analysis considers the dynamics of crowdfunding from two aspects: how fundraising activities and promotional activities on social media simultaneously evolve over time, and how the promotion campaigns influence the final outcomes. From our investigation, we identify a number of important principles that provide a useful guide for devising effective campaigns. For example, we observe temporal distribution of customer interest, strong correlations between a crowdfunding project's early promotional activities and the final outcomes, and the importance of concurrent promotion from multiple sources. We then show that these discoveries can help predict several important quantities, including overall popularity and the success rate of the project. Finally, we show how to use these discoveries to help design crowdfunding sites. Crowdfunding is changing how, why, and which ideas are brought into existence. With the increasing number of crowdfunded projects, it is important to understand what drives people to either create or fund these projects. To shed light on this new social phenomenon, we present a grounded theory of motivation informed by the first cross-platform qualitative study of the crowdfunding community. By performing 83 semistructured interviews, we uncover creator motivations, which include the desire to raise funds, expand awareness of work, connect with others, gain approval, maintain control, and learn; and supporter motivations, which include the desire to collect rewards, help others, support causes, and be part of a community. We also explore deterrents to crowdfunding participation, including, among creators, fear of failure, and, for supporters, lack of trust. Based on these findings, we provide three emergent design principles to inform the design of effective crowdfunding platforms and support tools. Crowdfunding websites such as Kickstarter are becoming increasingly popular, allowing project creators to raise hundreds of millions of dollars every year. However, only one out of two Kickstarter campaigns reaches its funding goal and is successful. It is therefore of prime importance, both for project creators and backers, to be able to know which campaigns are likely to succeed. We propose a method for predicting the success of Kickstarter campaigns by using both direct information and social features. We introduce a first set of predictors that uses the time series of money pledges to classify campaigns as probable success or failure and a second set that uses information gathered from tweets and Kickstarter's projects backers graph. We show that even though the predictors that are based solely on the amount of money pledged reach a high accuracy, combining them with predictors using social features enables us to improve the performance significantly. In particular, only 4 hours after the launch of a campaign, the combined predictor reaches an accuracy of more than 76 (a relative improvement of 4 ). Crowdfunding is a process by which enterprises or individuals seek to secure project funding by soliciting pledges from potential donors, usually via an Internet platform. These platforms offer project initiators the ability to limit the number of times a certain reward is claimed by supporters. This can be used to either offer a reward, which is naturally limited, or to induce an artificial scarcity for rewards without a natural limitation. The induction of such artificial limitations represents a signal which may, fundamentally, either have a positive or a negative effect on the crowdfunding project. To answer this question, this paper not only discusses the theoretical effects of scarcity management in the crowdfunding context, but also investigates this empirically. The analysis of 42,996 projects from Indiegogo.com indicates that current scarcity management is problematic at best and reduces the chances of projects to successfully achieve their target funding. Crowdfunding provides a new opportunity for entrepre-neurs to launch ventures without having to rely on traditional funding mechanisms, such as banks and angel investing. Despite its rapid growth, we understand little about how crowdfunding users build ad hoc online communities to undertake this new way of performing entrepreneurial work. To better understand this phenomenon, we performed a qualitative study of 47 entrepreneurs who use crowdfunding platforms to raise funds for their projects. We identify community efforts to support crowdfunding work, such as providing mentorship to novices, giving feedback on campaign presentation, and building a repository of example projects to serve as models. We also identify where community efforts and technologies succeed and fail at support-ing the work in order to inform the design of crowdfunding support tools and systems. Crowdfunding allows founders of for-profit, artistic, and cultural ventures to fund their efforts by drawing on relatively small contributions from a relatively large number of individuals using the internet, without standard financial intermediaries. Drawing on a dataset of over 48,500 projects with combined funding over $237 M, this paper offers a description of the underlying dynamics of success and failure among crowdfunded ventures. It suggests that personal networks and underlying project quality are associated with the success of crowdfunding efforts, and that geography is related to both the type of projects proposed and successful fundraising. Finally, I find that the vast majority of founders seem to fulfill their obligations to funders, but that over 75 deliver products later than expected, with the degree of delay predicted by the level and amount of funding a project receives. These results offer insight into the emerging phenomenon of crowdfunding, and also shed light more generally on the ways that the actions of founders may affect their ability to receive entrepreneurial financing. Crowdfunding is a process where commercial or non-commercial projects are initiated in a public announcement by organizations or individuals to receive funding, assess the market potential, and build customer relationships. Crowdfunding is employed in a variety of different categories, ranging from technology to arts and even disaster relief. Even though crowd-funding has received widespread attention, not only in the media, literature on the subject is still sparse and lacks especially empirical research. In contrast, research in new product preannouncement is established and more mature, and, due to similarities in process and goals, yields entry points for crowdfunding research. This paper contributes by reducing the gap in crowdfunding research by drawing on insights from new product preannouncement literature. To this end, a common definition of crowdfunding, which is currently lacking in literature, is derived and used to characterize commonalities with new product preannouncement. This theoretical discussion is complemented by empirically testing the derived hypotheses about common success factors. Conclusions are drawn from the logistic-regression, using the technology category of a project dataset with 45,400 observations. Research shows that while timing and communication are key success factors, common to both new product preannouncement and crowdfunding, other success factors may already be standard and cannot separate the successful crowdfunding projects from the unsuccessful.