Project Ideas slides modified from Eileen Kraemer and David P. Feldman.

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Presentation transcript:

Project Ideas slides modified from Eileen Kraemer and David P. Feldman

Examples of complex networks: geometric, regular

Examples of complex networks: semi-geometric, irregular

Elementary features: node diversity and dynamics

Elementary features: edge diversity and dynamics

Network Questions: Structural How many connections does the average node have? Are some nodes more connected than others? Is the entire network connected? On average, how many links are there between nodes? Are there clusters or groupings within which the connections are particularly strong? What is the best way to characterize a complex network? How can we tell if two networks are “different”? Are there useful ways of classifying or categorizing networks?

Network Questions: Communities Are there clusters or groupings within which the connections are particularly strong? What is the best way to discover communities, especially in large networks? How can we tell if these communities are statistically significant? What do these clusters tell us in specific applications?

Network Questions: Dynamics of How can we model the growth of networks? What are the important features of networks that our models should capture? Are there “universal” models of network growth? What details matter and what details don’t? To what extent are these models appropriate null models for statistical inference? What’s the deal with power laws, anyway?

Network Questions: Dynamics on How do diseases/computer viruses/innovations/ rumors/revolutions propagate on networks? What properties of networks are relevant to the answer of the above question? If you wanted to prevent (or encourage) spread of something on a network, what should you do? What types of networks are robust to random attack or failure? What types of networks are robust to directed attack? How are dynamics of and dynamics on coupled?

Network Questions: Algorithms What types of networks are searchable or navigable? What are good ways to visualize complex networks? How does google page rank work? If the Internet were to double in size, would it still work?

Network Questions: Algorithms There are also many domain-specific questions: Are networks a sensible way to think about gene regulation or protein interactions or food webs? What can social networks tell us about how people interact and form communities and make friends and enemies? Lots and lots of other theoretical and methodological questions... What else can be viewed as a network? Many applications await.

Network Questions: Outlook Advances in available data, computing speed, and algorithms have made it possible to apply network analysis to a vast and growing number of phenomena. This means that there is lots of exciting, novel work being done This work is a mixture of awesome, exploratory, misleading, irrelevant, relevant, fascinating, ground-breaking, important, and just plain wrong It is relatively easy to fool oneself into seeing thing that aren’t there when analyzing networks. This is the case with almost anything, not just networks For networks, how can we be more careful and scientific, and not just descriptive and empirical?