# Study of Information Dissemination in Hypernetworks with Adjustable Clustering Coefficient
## 5 Conclusions and Prospect  
In order to study the characteristics of information propagation in real social hypernetworks, a hypernetwork model and SIS propagation model based on the aggregation phenomenon were constructed. A theoretical analysis and simulation experiments were used to verify the hyperdegree distribution and the information propagation law under the aggregation phenomenon. The theoretical analysis and simulation experiments were in complete agreement. Although the proposed model clustering coefficients had no effect on the scalar law of the hyperdegree distribution, we know that in many real systems, especially social hypernetworks, power-law and high-aggregation phenomena often coexist. Most notably, the information propagation rate decreased with the increase in the clustering coefficient. The global dissemination of information was not significantly impacted by the magnitude of the hypernetwork scale, while individuals with more neighbors had a higher information dissemination ability, which had a greater impact on the early stage of information dissemination. Both spreading rate and recovering rate affected the information dissemination ability. The larger the spreading rate, the faster the information spread and the larger the steady-state value. The larger the recovering rate, the smaller the steady-state value, and the recovering rate had less influence on the rate of information dissemination. By analyzing the parameters of the network structure, it was found that the larger the number of newly added nodes, the larger the number of old nodes selected, the larger the number of new hyperedges generated each time, and the faster the information propagation. The effect of the number of old nodes was greater than the effect of the number of new nodes. This paper introduced a new research direction in information dissemination for hypernetwork models and developed a theoretical system for hypernetwork information dissemination, offering innovative ideas for hypernetwork studies. However, further  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multicolumn{2}{c}{**The Density of Informed Nodes (\(\rho\))**} \\ \cline{2-3}  & **Non-Steady State** & **Steady State** \\ \hline Nodes (\(N\
eq N^{\prime}\)) & \(\rho_{N}\approx\rho_{N^{\prime}}\) & \(\rho_{N}\approx\rho_{N^{\prime}}\) \\ Spreading seed & \(\rho_{maxDi}>\rho_{avgDi}>\rho_{minDi}\) & \(\rho_{maxDi}=\rho_{avgDi}=\rho_{minDi}\) \\ Clustering coefficient (\(P<p^{\prime}\)) & \(\rho_{P}>\rho_{P^{\prime}}\) & \(\rho_{P}=\rho_{P^{\prime}}\) \\ Clustering coefficient (\(P=0\)) & \(\rho_{AP}\ ^{1}=\rho_{BA}\) & \(\rho_{AP}=\rho_{BA}\) \\ Spreading rate (\(\beta<\beta^{\prime}\)) & \(\rho_{\beta}<\rho_{\beta^{\prime}}\) & \(\rho_{\beta}<\rho_{\beta^{\prime}}\) \\ Recovering rate (\(\gamma<\gamma^{\prime}\)) & \(\rho_{\gamma}\approx\rho_{\gamma^{\prime}}\) & \(\rho_{\gamma}>\rho_{\gamma^{\prime}}\) \\ New nodes (\(m_{1}<m_{1^{\prime}}\)) & \(\rho_{m_{1}}>\rho_{m_{1^{\prime}}}\) & \(\rho_{m_{1}}\approx\rho_{m_{1^{\prime}}}\) \\ Old nodes (\(m_{2}<m_{2^{\prime}}\)) & \(\rho_{m_{2}}<\rho_{m_{2^{\prime}}}\) & \(\rho_{m_{2}}<\rho_{m^{\prime}}\) \\ New hyperedges (\(m<m^{\prime}\)) & \(\rho_{m}<\rho_{m^{\prime}}\) & \(\rho_{m}<\rho_{m^{\prime}}\) \\ \(m_{1}=m_{2}\), (\(m_{1}+m_{2}\)) & \(\rho_{(m_{1}+m_{2})}<\rho_{(m_{1}+m_{2})^{\prime}}\) & \(\rho_{(m_{1}+m_{2})}<\rho_{(m_{1}+m_{2})}\) \\ \(m_{1}\
eq m_{2}\)investigation into the dissemination process is required to complement the current research. Thus, several potential future research directions are proposed as follows:  
1. The hypernetwork structure is based on \(k\)-uniform hypergraphs. The number of individuals in a social hypernetwork is usually different, and it remains to be further investigated whether there are unique information dissemination characteristics on nonuniform hypergraphs based on aggregation phenomena. 2. The information dissemination discussed in this paper is based on a static hypernetwork.