Target-Dependent Churn Classification in Microblogs

In particular, we investigate demographic business. Banks, telecommunication companies, airlines, Internet churn indicators (obtained from users of microposts), service providers, pay TV companies, and insurance content churn indicators (obtained from the textual firms etc., utilize customer churn or attrition rates as one of content of micro-posts), and context churn indicators (obtained their key business metrics. This metric is important as the from threads containing the micro-posts). We examine churn rate of a business is a good indicator of customer response factors that make this problem more challenging and investigate to services, pricing, and competitions. The ability to the performance of several state-of-the-art machine identify churny contents / behaviors can enable early intervention learning techniques on this problem. A challenging aspect processes (as part of retention campaigns) and ultimately of such classification task is that churny contents can be expressed a reduction in customer churn.