Abstract
With the development of modern technology(communication, transportation, etc.), many new social networks have formed and influenced our life. The research of mining these new social networks has been used in many aspects. But compared with traditional networks, these new social networks are usually very large. Due to the complexity of the latter, few model can be adapted to mine them effectively. In this paper, we try to mine these new social networks using Wave Propagation process and mainly discuss two applications of our model, solving Message Broadcasting problem and Rumor Spreading problem. Our model has the following advantages: (1) We can simulate the real networks message transmitting process in time since we include a time factor in our model. (2) Our Message Broadcasting algorithm can mine the underlying relationship of real networks and represent some clustering properties. (3) We also provide an algorithm to detect social network and find the rumor makers. Complexity analysis shows our algorithms are scalable for large social network and stable analysis proofs our algorithms are stable.
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Acknowledgements
The work is partially supported by Natural Science Foundation of China (No. 11001237) and NUDT Preparing Research Project JC-02-01-04.
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Wang, X., Tao, H., Xie, Z. et al. Mining social networks using wave propagation. Comput Math Organ Theory 19, 569–579 (2013). https://doi.org/10.1007/s10588-012-9142-x
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DOI: https://doi.org/10.1007/s10588-012-9142-x