korrents

network science

Why systems as different as a genome and the web share the same connection patterns.

What people on korrents have said about network science, newest first — 9 positions from 3 people.

FilterEveryone, all time
Who Everyone ABAlbert-László Barabási 4 RARéka Albert 4 BGBill Gurley 1
When All time Past 1 yearPast 3 yearsPast 5 years
  1. BG

    Bill Gurley quoted

    Our readingInvestors have collectively absorbed the idea of increasing returns and power laws, and that belief is what makes them take ever more risk.

    Their wordsthe investor community writ large has slowly become aware of and believes it strongly in increasing returns and power laws. And so over time, if they all believe that, they're going to be more willing to invest on the come and take risk.

    ↗Mental Models That Change How You Think | Bill Gurleyyoutube.com 8th of 16 in this recording

    investing

    Interesting
  2. 27 years earlier
  3. AB

    Albert-László Barabási quoted

    Our readingSystems as different as a genome and the web are best described as networks with complex topology rather than as ordered or random structures.

    Their wordsSystems as diverse as genetic networks or the world wide web are best described as networks with complex topology.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 1st of 8 in this piece

    Interesting
  5. RA

    Réka Albert quoted

    Our readingSystems as different as a genome and the web are best described as networks with complex topology rather than as ordered or random structures.

    Their wordsSystems as diverse as genetic networks or the world wide web are best described as networks with complex topology.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 2nd of 8 in this piece

    Interesting
  7. AB

    Albert-László Barabási quoted

    Our readingLarge real-world networks share one property: the number of connections per node follows a scale-free power law.

    Their wordsA common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 3rd of 8 in this piece

    Interesting
  9. RA

    Réka Albert quoted

    Our readingLarge real-world networks share one property: the number of connections per node follows a scale-free power law.

    Their wordsA common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 4th of 8 in this piece

    Interesting
  11. AB

    Albert-László Barabási quoted

    Our readingScale-free structure follows from just two mechanisms: networks keep adding nodes, and new nodes attach preferentially to well-connected ones.

    Their wordsThis feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 5th of 8 in this piece

    Interesting
  13. RA

    Réka Albert quoted

    Our readingScale-free structure follows from just two mechanisms: networks keep adding nodes, and new nodes attach preferentially to well-connected ones.

    Their wordsThis feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 6th of 8 in this piece

    Interesting
  15. AB

    Albert-László Barabási quoted

    Our readingBecause two generic mechanisms reproduce the observed distributions, large networks are governed by self-organizing rules that do not depend on what the network is made of.

    Their wordsA model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 7th of 8 in this piece

    Interesting
  17. RA

    Réka Albert quoted

    Our readingBecause two generic mechanisms reproduce the observed distributions, large networks are governed by self-organizing rules that do not depend on what the network is made of.

    Their wordsA model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

    ↗Barabasi & Albert, "Emergence of scaling in random networks" (arXiv)arxiv.org 8th of 8 in this piece

    Interesting