Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Targeted online advertising elicits a potential threat. A commercial agent has a chance to mitigate the visibility of his opponents because their sales or services are of similar types. ,  consider the competition for attention in popular online social networks (OSNs) that usually employ a timeline-based homepage to sort messages chronologically in a limited visible region. A non-cooperative Tullock-like game model is formulated that consists of a finite amount of \emph{benign} agents and one \emph{malicious} agent. By paying to the OSN, each benign agent seeks to maximize his utility of visibility, while the malicious one aims to reduce the utilities of benign agents. Our primary purposes are to quantify how robust the overall performance of benign agents is against the malicious action, and how the OSN's revenue is influenced.  derive the upper and the lor bounds of six fundamental measures with regard to the total utility and the total net utility of benign agents and the OSN's revenue under three different scenarios: with and without the malicious agent, and the maximum. They capture the worst and the best performances of the benign agents as ll as the OSN. Our study reveals two important insights: i) the performance bounds are very sensitive to the malicious agent's willingness to pay at certain ranges; ii) the OSN acquires more revenues from this malicious action.
['Yuedong Xu', 'Zhujun Xiao', 'Tianyu Ni', 'Xin Wang', 'Eitan Altman']
I am writing a research paper on a idea Efficiency of Adversarial Timeline Competition in Online Social Networks
[{"from": "human", "value": "I am writing a research paper on a idea Efficiency of Adversarial Timeline Competition in Online Social Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Targeted online advertising elicits a potential threat. A commercial agent has a chance to mitigate the visibility of his opponents because their sales or services are of similar types. ,  consider the competition for attention in popular online social networks (OSNs) that usually employ a timeline-based homepage to sort messages chronologically in a limited visible region. A non-cooperative Tullock-like game model is formulated that consists of a finite amount of \\emph{benign} agents and one \\emph{malicious} agent. By paying to the OSN, each benign agent seeks to maximize his utility of visibility, while the malicious one aims to reduce the utilities of benign agents. Our primary purposes are to quantify how robust the overall performance of benign agents is against the malicious action, and how the OSN's revenue is influenced.  derive the upper and the lor bounds of six fundamental measures with regard to the total utility and the total net utility of benign agents and the OSN's revenue under three different scenarios: with and without the malicious agent, and the maximum. They capture the worst and the best performances of the benign agents as ll as the OSN. Our study reveals two important insights: i) the performance bounds are very sensitive to the malicious agent's willingness to pay at certain ranges; ii) the OSN acquires more revenues from this malicious action."}]