Abstract
Measurement studies of online social networks show that all social links are not equal, and the strength of each link is best characterized by the frequency of interactions between the linked users.To date, few studies have been able to examine detailed interaction data over time, and none have studied the problem of modeling user interactions. This paper proposes a generative model of social interactions that captures the inherently heterogeneous strengths of social links, thus having broad implications on the design of social network algorithms such as friend recommendation, information diffusion and viral marketing.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
