A Comprehensive Algorithm for Evaluating Node Influences in Social Networks Based on Preference Analysis and Random Walk

In the era of big data, social network has become an important reflection of human communications and interactions on the Internet. Identifying the influential spreaders in networks plays a crucial role in various areas, such as disease outbreak, virus propagation, and public opinion controlling. Based on the three basic centrality measures, a comprehensive algorithm named PARW-Rank for evaluating node influences has been proposed by applying preference relation analysis and random walk technique. For each basic measure, the preference relation between every node pair in a network is analyzed to construct the partial preference graph (PPG). Then, the comprehensive preference graph (CPG) is generated by combining the preference relations with respect to three basic measures. Finally, the ranking of nodes is determined by conducting random walk on the CPG. Furthermore, five public social networks are used for comparative analysis. The experimental results show that our PARW-Rank algorithm can achieve the higher precision and better stability than the existing methods with a single centrality measure.

Unstable predator–prey dynamics permits the coexistence of generalist and specialist predators, and the maintenance of partial preferences

Saturating functional responses are a unifying principle in ecology, influencing processes at organizational levels from dietary specialization in individuals, to population instability, to community-level indirect interactions among alternative prey. These effects are interrelated. We explore a predator–prey model and demonstrate that unstable dynamics promote coexistence of specialist and generalist predators, when the specialist attacks only high-quality prey, and the generalist attacks high- and low-quality prey (that alone cannot maintain the predator). Coexisting specialist and generalist predators are vulnerable to invasion and replacement by predators with fixed partial preferences. The evolutionarily stable partial preference increases with increasing dynamic instability, but typically declines with increasing abundance of the low-quality prey. Coexisting specialist and generalist consumers, or partial preferences, typically reduce the potential for poor-quality prey to indirectly benefit high-quality prey. We suggest that dynamic instability may also contribute to the evolutionary maintenance of seemingly maladaptive oviposition choices by insect parasitoids.