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Cultural communication in double-layer coupling social network based on association rules in big data
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Cultural communication in double-layer coupling social network based on association rules in big data
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Journal Article
Cultural communication in double-layer coupling social network based on association rules in big data
2020
Overview
In the big data set around the world, cultural communication in a single-layer social network cannot handle data in a two-tier social network. Combined with the characteristics of cultural communication, a two-layer coupled social network model for predicting cultural information dissemination is proposed. According to the law of big data set in the process of cultural communication, the ethical review and theoretical construction of cultural network communication was carried out. Combining the online two-layer coupling network and the CRF word segmentation algorithm, the known link relationship is obtained, and the feature attributes of the network are extracted. This paper mainly completed the construction of online social network link prediction. Starting from the topological structure of two-layer coupled social network, based on the association rules to analyze the data generated by information dissemination between two-layer coupled network nodes, a two-layer coupled network information propagation law model is proposed. The prediction and construction of the cultural information communication link in the online social network is completed, the process of data opening and sharing is accelerated, and the privacy and copyright issues in the process of cultural communication are solved. The influence of immune node and node self-healing time on the cultural information dissemination process of two-layer coupled social network is discussed. By comparing the information dissemination in social networks and the information dissemination in two-layer coupled social networks, the control of certain lyric cultures can be effectively prevented. The experimental results show that it has reference value.
Publisher
Springer Nature B.V
Subject
