Enterprise Social Link Recommendation

Abstract

Many companies have started to use Enterprise Social Networks (ESNs), such as Yammer, to facilitate collaboration and communication amongst their employees in the business context. Social link recommendation, which finds and suggests whom one wants to connect with in a company, is crucial for ESNs to promote their usages. Although link recommendation has been studied extensively in external social networks (e.g., Facebook and Twitter), it has not been addressed in ESNs. In this paper, we study this novel problem. Social link recommendation in ESNs is significantly different from that in external social networks, and also has unique challenges: (1) people usually socialize differently in enterprise than in their personal life, but users' social behaviors in enterprise have not been well explored, and (2) there is important business information available in ESNs under the enterprise context, e.g., a company?s organizational chart, but how to exploit it for link recommendation is still an open problem. To this end, we mine not only the social graph and user-generated content in ESNs, but also the company's organizational chart, to model enterprise user social behaviors. We develop a supervised link recommendation algorithm using a large scale enterprise social network based on Yammer (with over 100k users), which shows that the proposed techniques perform effectively. Moreover, we find that both the social graph and the organizational chart are complementary to each other for link recommendation in ESNs.