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Sociocentric and egocentric measures for identifying the key players in telecom social network

机译:用于识别电信社交网络中的关键播放器的社会中心和自主化措施

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Telecom Social Network Analysis (TSNA) is an upcoming and interesting area of concern in telecom industries since it not only helps in exploring the information regarding the social network of subscribers but also helps the operators' to focus on their business analytics. TSNA is being used to give a solution to some of the telecom problems such as to improve churn prediction, overall customer satisfaction and retention. Since the structure of social networks provides the natural way to understand customers' relationships and the behavior of groups of highly connected customers. The typical work on social network analysis includes the construction of both multirelational telecom social networks and ego-networks of telecom customers for discovery of group of customers who share similar properties and classify the customers as churners and non-churners. This paper explores both sociocentric and egocentric methods for identifying key players who plays important roles in decision making in finding the churn rate of telecom social networks.
机译:电信社交网络分析(TSNA)是电信行业的即将举行和有趣的关注领域,因为它不仅有助于探索有关订阅者的社交网络的信息,而且有助于运营商专注于他们的业务分析。 TSNA正在用于对一些电信问题的解决方案,以提高流失预测,整体客户满意度和保留。由于社交网络的结构提供了了解客户的关系和高度关联客户组的行为的自然方式。社交网络分析的典型工作包括建造多界电信社交网络和电信客户的自我网络,以发现分享类似属性的客户组,并将客户作为搅拌器和非搅拌器分类。本文探讨了社会中心和自主特神经方法,用于识别在决策中发挥重要作用的关键参与者,以寻找电信社交网络的流失率。

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