Generally Real Networks do not behave according to the Random Networks Model, even so, they can share some properties. Analyse the following statements.
- The degree distribution of a network can be closely aproximated as a Poisson distribution;
- At \(\left \langle k \right \rangle\) > 1, it exists a giant component in the network;
- Average path length can be predicted as \(\left \langle d \right \rangle = \frac{ln N}{ln \left \langle k \right \rangle}\) and can present Small World property;
- The average clustering coefficient \(\left \langle c \right \rangle\) generally appears to be independent of the number of nodes N.
Which option contains the true statements for Random Networks that can be found also in general Real Networks?
- I and IV;
- II and III;
- II and IV;
- I, II and III;
- None of the above.
Original idea by: Fillipi Valadares
Interesting question, but I'm afraid it get too general, trying to speak about real networks (meaning, *all* real networks). It's very hard to state something useful and valid for all real networks.
ReplyDeleteAdding “generally” wouldn’t make it more comprehensive?
DeleteEdited the question to make clear that we do not mean for all Real Networks, but for general Real Networks.
DeleteHi Fillipi. The question improved, but it is still ambiguous, in my opinion. Very hard to answer. Why don't you compare random networks with scale-free networks, instead of 'real' networks, which are much harder to characterize?
ReplyDelete