Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents several measures of fairness and inequality based on the degree distribution in networks, as alternatives to the ll-established por-law exponent. Networks such as social networks, communication networks and the World Wide b itself are often characterized by their unequal distribution of edges: Few nodes are attached to many edges, while many nodes are attached to only few edges. The inequality of such network structures is typically measured using the por-law exponent, stating that the number of nodes with a given degree is proportional to that degree taken to a certain exponent. Hover, this approach has several aknesses, such as its narrow applicability and expensive computational complexity. Beyond the fact that por laws are by far not a universal phenomenon on the b, the por-law exponent has the surprising property of being  negatively  correlated with the usual notion of inequality, making it unintuitive as a fairness measure. As alternatives,  propose several measures based on the Lorenz curve, which is used in economics but rarely in networks study, and on the information-theoretical concept of entropy.  show in experiments on a large collection of online networks that these measures do not suffer under the drawbacks of the por-law exponent.
['Jérôme Kunegis', 'Julia Preusse']
I am writing a research paper on a idea Fairness on the web: alternatives to the power law
[{"from": "human", "value": "I am writing a research paper on a idea Fairness on the web: alternatives to the power law"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents several measures of fairness and inequality based on the degree distribution in networks, as alternatives to the ll-established por-law exponent. Networks such as social networks, communication networks and the World Wide b itself are often characterized by their unequal distribution of edges: Few nodes are attached to many edges, while many nodes are attached to only few edges. The inequality of such network structures is typically measured using the por-law exponent, stating that the number of nodes with a given degree is proportional to that degree taken to a certain exponent. Hover, this approach has several aknesses, such as its narrow applicability and expensive computational complexity. Beyond the fact that por laws are by far not a universal phenomenon on the b, the por-law exponent has the surprising property of being  negatively  correlated with the usual notion of inequality, making it unintuitive as a fairness measure. As alternatives,  propose several measures based on the Lorenz curve, which is used in economics but rarely in networks study, and on the information-theoretical concept of entropy.  show in experiments on a large collection of online networks that these measures do not suffer under the drawbacks of the por-law exponent."}]