Abstract
With the popularity of social network, information propagation prediction based on social network is also becoming popular. As far as we know, people do not concern the user who forwards its own microblog in information propagation prediction. In our investigation the self forward behavior can cause the further spreading of the information. Thus in this paper we propose a self forward prediction model to predict the self forward behavior. We use ELM to train and predict self forward behavior. Based on this model we proposed an algorithm to predict the information dissemination. The experiment results show that our algorithm is real and effective and it significantly improves the forecast accuracy. It also can be seen in the experimental results that the results of ELM has a better performance than SVM.
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Notes
- 1.
ELM Source Codes: ELM Source Codes: http://www.ntu.edu.sg/home/egbhuang/.
- 2.
Data set: http://www.csie.ntu.edu.tw/cjlin/libsvm/.
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Acknowledgments
This research was partially supported by the National Natural Science Foundation of China under Grant Nos. 61332006 and 61100022; the National BasicResearch Program of China under Grant No. 2011CB302200-G; the 863 Program under Grant No. 2012AA011004. The researcher claims noconflicts of interests.
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Liu, H., Li, Y., Liu, H. (2016). Self Forward and Information Dissemination Prediction Research in SINA Microblog Using ELM. In: Cao, J., Mao, K., Wu, J., Lendasse, A. (eds) Proceedings of ELM-2015 Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-28373-9_11
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DOI: https://doi.org/10.1007/978-3-319-28373-9_11
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