Abstract
With the rapid development of social network, the information announced by this platform attracts more and more attention, because of the great harm brought by the false information, researching the false information detection of social network has great significance. This paper presents a model of social network false information detection, which firstly converting the information announced by social network into a three-dimensional vector, then comparing this vector with the three-dimensional vector converted by Internet events and calculating the similarity between social network and Internet, detecting the consistency of social network event and Internet event afterwards, finally gathering statistics and analyzing then we can get the similarity between social network event and Internet event, according to this, we can judge that the social network information is false or not.
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Acknowledgments
The author thanks the editor and reviewers for their suggestions to improve the quality of paper. This work was supported by the National Key Research and Development Program of China under Grant 2016YFB0800404 and NSF of China (U1536118) and NSF of China (U1433105).
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Xu, Y., Li, F., Liu, J., Zhang, R., Yao, Y., Zhang, D. (2017). Detecting False Information of Social Network in Big Data. In: Wang, S., Zhou, A. (eds) Collaborate Computing: Networking, Applications and Worksharing. CollaborateCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 201. Springer, Cham. https://doi.org/10.1007/978-3-319-59288-6_65
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DOI: https://doi.org/10.1007/978-3-319-59288-6_65
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