Abstract
With the growth of online social media, such as Twitter and Weibo, topic diffusion has concerned a lot attention. Based on the timing sequence and retweet relationship, the propagation history of one single Weibo have been rebuilt successfully in social network with various methods. However, the topic diffusion among users can hardly be reconstructed, as vast of different content Weibo need to be consider. In this paper, the authors propose a user topic diffusion history reconstruction method to reconstruct the propagation process of a topic. Based on the topic detection algorithm, different weibo can be clustered to a group as the data set. A score-based propagated model is proposed to obtain the information source node in a back propagation way with considering the influence of time, social relationship and text similarity.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 61472433) and the National Basic Research Program of China (“973” Program, No. 2013CB329604).
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Song, Y., Li, A., Huang, J., Quan, Y., Deng, L. (2017). History Path Reconstruction Analysis of Topic Diffusion on Microblog. In: Xhafa, F., Patnaik, S., Yu, Z. (eds) Recent Developments in Intelligent Systems and Interactive Applications. IISA 2016. Advances in Intelligent Systems and Computing, vol 541. Springer, Cham. https://doi.org/10.1007/978-3-319-49568-2_21
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DOI: https://doi.org/10.1007/978-3-319-49568-2_21
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