Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Diffusion of information in social networks takes more and more attention from marketers. New methods and algorithms are constantly developed towards maximizing reach of the campaigns and increasing their effectiveness. One of the important research directions in this area is related to selecting initial nodes of the campaign to result with maximizing its effects represented as total number of infections. To achieve this goal, several strategies re developed and they are based on different network measures and other characteristics of users. The problem is that most of these strategies base on static network properties while typical online networks change over time and are sensitive to varying activity of users. In this work a novel strategy is proposed which is based on multiple measures with additional parameters related to nodes availability in time periods prior to the campaign. Presented results show that it is possible to compensate users with high network measures by others having high frequency of system usage, which, instead, may be easier or cheaper to acquire.
['Jarosław Jankowski', 'Radosław Michalski', 'Przemysław Kazienko']
I am writing a research paper on a idea Compensatory seeding in networks with varying avaliability of nodes
[{"from": "human", "value": "I am writing a research paper on a idea Compensatory seeding in networks with varying avaliability of nodes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Diffusion of information in social networks takes more and more attention from marketers. New methods and algorithms are constantly developed towards maximizing reach of the campaigns and increasing their effectiveness. One of the important research directions in this area is related to selecting initial nodes of the campaign to result with maximizing its effects represented as total number of infections. To achieve this goal, several strategies re developed and they are based on different network measures and other characteristics of users. The problem is that most of these strategies base on static network properties while typical online networks change over time and are sensitive to varying activity of users. In this work a novel strategy is proposed which is based on multiple measures with additional parameters related to nodes availability in time periods prior to the campaign. Presented results show that it is possible to compensate users with high network measures by others having high frequency of system usage, which, instead, may be easier or cheaper to acquire."}]