Abstract
How to predict the influence of users in micro-blog is a challenging task. Although numerous attempts have been made for this topic, few of them analyze the influence of users from the perspective filtration mechanism. In this paper, we propose a novel Activation Forwarding Relationship Independent Cascade algorithm for analyzing the influence of users. The algorithm mainly consists of two parts: forwarding prediction and activation process. We predict the forwarding relationship by Random Forest (RF) and improve the Independent Cascade algorithm to construct an activation network. The algorithm can filter non influence users during the construction of the activation network, thus reducing the amount of ranking time. By calculating the user’s activation capability, we rank user’s influence. The experimental results show that our algorithm can achieve 95% accuracy in predicting forwarding relationships. Besides, our algorithm not only saves computing time, but also shows that the Top-10 users in the ranking list have better ability to spread information than the existing ranking algorithms.
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Acknowledgements
This work was partly supported by the NSFC-Guangdong Joint Found (U1501254) and the Co-construction Program with the Beijing Municipal Commission of Education and the Ministry of Science and Technology of China (2012BAH45B01) and National key research and development program (2016YFB0800302) the Director’s Project Fund of Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education (Grant No. 2017ZR01) and the Fundamental Research Funds for the Central Universities (BUPT2011RCZJ16, 2014ZD03-03) and China Information Security Special Fund (NDRC).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Yang, Y., Yao, W., Wang, D. (2018). Ranking the Influence of Micro-blog Users Based on Activation Forwarding Relationship. In: Romdhani, I., Shu, L., Takahiro, H., Zhou, Z., Gordon, T., Zeng, D. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-030-00916-8_36
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DOI: https://doi.org/10.1007/978-3-030-00916-8_36
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