Identifying Subscribers in Freemium E-commerce Model Based on Support Vector Classification

摘要

Advances in information technologies have brought many changes to our lives. Finding free music through online platform rather than buying hard copies offline is one of the most significant changes. Recent researches suggest that as users becoming more engaged with the online content-provider platform, they are more willing to pay for the service or premium service. This study addresses the need of freemium e-commerce identifying potential subscribers. In specific, we propose a novel method, namely support vector classification (SVC), to categorize content viewers into potential subscriber and non-potential subscribers. Our method provides satisfied prediction result and the experiment showed that SVC is a superior method in this kind of task.