Abstract
The spread of information, opinions, preferences, and behavior across social media is a crucial feature of the current functioning of our economy, politics, and culture. One of the emerging channels for spreading social collective action and funding of novelty in all these domains is Crowdfunding on various platforms such as Kickstarter, Indiegogo, Sellaband, and may others. The exact spreading mechanism of this collective action is not well-understood. The general belief is that virality plays a crucial role. Namely, the common hypothesis is that the information or behavior propagates through individuals affecting one another, presumably, through the links connecting them in social networks. The aim of our study is to find out the actual spreading mechanism in one particular case: spread of financial support for individual Kickstarter campaigns. To our surprise, our studies show that “virality” plays here only a minor role. We used this result to construct a simple behavior-grounded stochastic predictor of the success of Kickstarter campaigns which is not based on the viral mechanism. The crucial feature of the model underlying the prediction algorithm is that the success of a campaign depends less on the backers influencing one another (“virality”) but rather on the campaign appealing to a particular class of high-pledge backers. This appeal is usually revealed at the very beginning of the campaign and it is an excellent success predictor. The case of Kickstarter is consistent with a recently proposed generic hypothesis that popularity in social media arises more from independent responses by individuals belonging to a large homophily class rather than from percolation, self-exciting processes, and other cooperative mechanisms resulting from mutual influence between individuals. Thus, the very concept of “virality”, which implies contagion between participating individuals, plays only a minor role in the success mechanism proposed hereby. A more appropriate term for the mechanism underlying the social success in our model could be “social appeal” or “social fitness”.
Highlights
Introduction and key findingsPredicting collective human behavior is a very difficult task because the causes at the individual level are often not directly recognizable from the systemic outcome.Previous works uncovered a series of feedback mechanisms amplifying “microscopic”/individual inputs to the level of systemic transformations: multiplicative dynamics (Levy and Solomon, 1996), social percolation (Solomon et al, 2000), herding (Levy et al, 1994)
We found that the success of a Kickstarter campaign depends on the arousal of a special type of backers’ behavior which can be inferred from the analysis of the statistical distribution of pledges
We found that the dynamics of pledge accumulation depends more on q(t) rather than on the target pledge Q0, this reduction is justified
Summary
Introduction and key findingsPredicting collective human behavior is a very difficult task because the causes at the individual level (reciprocal influences, groups of individuals with similar behavior) are often not directly recognizable from the systemic outcome.Previous works uncovered a series of feedback mechanisms amplifying “microscopic”/individual inputs to the level of systemic transformations: multiplicative dynamics (Levy and Solomon, 1996), social percolation (Solomon et al, 2000), herding (Levy et al, 1994). Predicting collective human behavior is a very difficult task because the causes at the individual level (reciprocal influences, groups of individuals with similar behavior) are often not directly recognizable from the systemic outcome. We found that the success of a Kickstarter campaign depends on the arousal of a special type of backers’ behavior which can be inferred from the analysis of the statistical distribution of pledges. From the very first day, the successful campaigns display a “fat tail” distribution which follows a power-law dependence (straight line in the double-logarithmic plot of Fig. 2a). The failed campaigns display much narrower exponential pledge distributions (straight lines in the semi-logarithmic plot of Fig. 2b)
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