Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Can  cluster blogs into types by considering their typical posting and linking behavior? How do blogs evolve over time? In this work  ansr these questions, by providing several sets of blog and post features that can help distinguish beten blogs. The first two sets of features focus on the topology of the cascades that the blogs are involved in, and the last set of features focuses on the temporal evolution, using chaotic and fractal ideas.  also propose to use PCA to reduce dimensionality, so that  can visualize the resulting clouds of points.  run all our proposed tools on the icwsm dataset. Our findings are that (a) topology features can help us distinguish blogs, like ‘humor’ versus ‘conservative’ blogs (b) the temporal activity of blogs is very non-uniform and bursty but (c) surprisingly often, it is self-similar and thus can be compactly characterized by the so-called bias factor (the ‘80’ in a recursive 80-20 distribution).
['Mary McGlohon', 'Jure Leskovec', 'Christos Faloutsos', 'Matthew Hurst', 'Natalie S. Glance']
I am writing a research paper on a idea Finding patterns in blog shapes and blog evolution
[{"from": "human", "value": "I am writing a research paper on a idea Finding patterns in blog shapes and blog evolution"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Can  cluster blogs into types by considering their typical posting and linking behavior? How do blogs evolve over time? In this work  ansr these questions, by providing several sets of blog and post features that can help distinguish beten blogs. The first two sets of features focus on the topology of the cascades that the blogs are involved in, and the last set of features focuses on the temporal evolution, using chaotic and fractal ideas.  also propose to use PCA to reduce dimensionality, so that  can visualize the resulting clouds of points.  run all our proposed tools on the icwsm dataset. Our findings are that (a) topology features can help us distinguish blogs, like \u2018humor\u2019 versus \u2018conservative\u2019 blogs (b) the temporal activity of blogs is very non-uniform and bursty but (c) surprisingly often, it is self-similar and thus can be compactly characterized by the so-called bias factor (the \u201880\u2019 in a recursive 80-20 distribution)."}]