Research on maximizing real demand response based on link addition in social networks

The impact of social networks on real-life scenarios is intensifying with the diversification of the information they disseminate. Consequently, the interconnection between social networks and tangible networks is strengthening. Notably, we have observed that messages disseminated on social networks, particularly those soliciting aid, exert a significant influence on the underlying network structure. This study aims to investigate the role and importance of social networks in the information dissemination process, as well as to construct a linear threshold model tailored for the dissemination of emergency information across both real and social networks, leveraging conventional models of information spread. We have developed a model to increase the number of connection edges in social networks in order to enhance their worth. Additionally, we discovered that the objective function possesses submodular features and thus the created problem is NP-hard. As a result, we can use algorithms with approximative assurances of $1-e^{-1}-{\theta }^{\prime }$ to solve our problem and ensures the accuracy of the solution. We also analyze the complexity of the algorithm in solving this problem. Finally we validated our conclusions with three publicly available datasets and one real data set to analysis the results of the solution.