Modeling the User Influence in the Expansion of Diffusion on Twitter

Social networks are a social structure of individuals and relationships between them that plays an important role in the spreading of information in today's world. Appearance and the spread of this type of networks on the internet new media for spreading information and news between the people of a community is provided.Understanding how information, product, idea, etc., to be published among users in online social networks, for many applications, such as viral marketing, online advertising, content ranking, and recommendation filtering it is very important. While different models for production online social network is static, but dynamic of user interactions through online social networks based on applications remains largely unknown.In this paper, given that information in the real world is dynamic, a probabilistic model to expand cascades / diffusion according invitation is surveyed: users actively inviting to join your neighbors in a cascade, by sending (possibly) multiple invitation messages. In this paper, a cascade model that describes the diffusion based-invitation, extraction and maximum likelihood estimator for understanding model's parameters formulated. In order to evaluate proposed model have performed the different experiments on Twitter data. Simulation results show that has been obtained parameters of the proposed method is closer to real world and then other methods have high accuracy.

کلیدواژه ها:

online social networks ، cascade ، diffusion ، invitation ، recruitment