Abstract
A person is considered as an influential individual when his behaviors can trigger other people's reactions. Such phenomenon is called user influence in social networks. Measuring user influence provides insights into dynamics of social network interactions. This makes a fundamental step for constructing marketing strategy, recommendation systems and so on. There have been various studies focusing on this problem. However, it lacks of a satisfactory method to measure user influence in a reasonable way. It is also worth studying on user properties and past activities that contribute to the influence of each user. In this paper, we investigate the attributes of millions of social network users and the content of their messages in order to better predict user influence. These users and messages are from Sina Weibo, which is one of the most popular social networks in China. Our first contribution is to quantify the influence of individuals within a period of time by using a new approach and find the individual influence of most users changing over time, but most changes are not significant. Our second contribution is to propose a phrase merging algorithm for obtaining high-quality phrases, which are very helpful for extracting the topics that each user is interested in. Our third contribution is to predict the influence of each user with a higher precision.
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.
