We present a novel framework to predict the success of Kickstarter campaigns based on the emotional intensity induced by domain specific aspects. The framework enables to automatically mine (from campaign descriptions and product reviews) clusters of aspects characterizing a domain of interest. A Need Index-based model is built in order to predict whether a campaign will result in success (i.e., reach its funding goal). The easy to interpret Need Index representation enables to understand and monitor the most relevant domain aspects and their related emotional intensities. We tested our framework on Kickstarter campaigns in the dominant domain of mobile games with a prediction accuracy of 94.4%. The methodology opens new ground for further interdisciplinary research on causal inference to support predictions related to customer needs, particularly in the areas of behavioural economics, marketing, brand management and market research.
Emotional Intensity-based Success Prediction Model for Crowdfunded Campaigns / Faralli, S.; Rittinghaus, S.; Samsami, N.; Distante, D.; Rocha, E.. - In: INFORMATION PROCESSING & MANAGEMENT. - ISSN 0306-4573. - 58:1(2021), pp. 1-21. [10.1016/j.ipm.2020.102394]
Emotional Intensity-based Success Prediction Model for Crowdfunded Campaigns
Faralli S.
Co-primo
;Distante D.
Co-primo
;
2021
Abstract
We present a novel framework to predict the success of Kickstarter campaigns based on the emotional intensity induced by domain specific aspects. The framework enables to automatically mine (from campaign descriptions and product reviews) clusters of aspects characterizing a domain of interest. A Need Index-based model is built in order to predict whether a campaign will result in success (i.e., reach its funding goal). The easy to interpret Need Index representation enables to understand and monitor the most relevant domain aspects and their related emotional intensities. We tested our framework on Kickstarter campaigns in the dominant domain of mobile games with a prediction accuracy of 94.4%. The methodology opens new ground for further interdisciplinary research on causal inference to support predictions related to customer needs, particularly in the areas of behavioural economics, marketing, brand management and market research.File | Dimensione | Formato | |
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