Skip to main content

Accelerated Information Dissemination on Networks with Local and Global Edges

  • Conference paper
  • First Online:
Structural Information and Communication Complexity (SIROCCO 2022)

Abstract

Bootstrap percolation is a classical model for the spread of information in a network. In the round-based version, nodes of an undirected graph become active once at least r neighbors were active in the previous round. We propose the perturbed percolation process: a superposition of two percolation processes on the same node set. One process acts on a local graph with activation threshold 1, the other acts on a global graph with threshold r – representing local and global edges, respectively. We consider grid-like local graphs and expanders as global graphs on n nodes.

For the extreme case \(r = 1\), all nodes are active after \(O(\log n)\) rounds, while the process spreads only polynomially fast for the other extreme case \(r \ge n\). For a range of suitable values of r, we prove that the process exhibits both phases of the above extremes: It starts with a polynomial growth and eventually transitions from at most cn to n active nodes, for some constant \(c \in (0, 1)\), in \(O(\log n)\) rounds. We observe this behavior also empirically, considering additional global-graph models.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ajazi, F., Napolitano, G.M., Turova, T.: Phase transition in random distance graphs on the torus. J. Appl. Probabil. 1278–1294 (2017)

    Google Scholar 

  2. Albert, R., Barabási, A.-L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)

    Article  MathSciNet  Google Scholar 

  3. Alon, N., Spencer, J.H.: The Probabilistic Method, 4th edn. Wiley, Hoboken (2016)

    Google Scholar 

  4. Abdullah, M.A., Fountoulakis, N.: A phase transition in the evolution of bootstrap percolation processes on preferential attachment graphs. Random Struct. Algorithms 52(3), 379–418 (2018)

    Google Scholar 

  5. Amini, H., Fountoulakis, N.: Bootstrap percolation in power-law random graphs. J. Stat. Phys. 155(1), 72–92 (2014)

    Article  MathSciNet  Google Scholar 

  6. Ball, F.: Stochastic and deterministic models for SIS epidemics among a population partitioned into households. Math. Biosci. 156(1–2), 41–67 (1999)

    Article  MathSciNet  Google Scholar 

  7. Ball, F., Neal, P.: A general model for stochastic SIR epidemics with two levels of mixing. Math. Biosci. 180(1–2), 73–102 (2002)

    Article  MathSciNet  Google Scholar 

  8. Ball, F., Neal, P.: Network epidemic models with two levels of mixing. Math. Biosci. 212(1), 69–87 (2008)

    Article  MathSciNet  Google Scholar 

  9. Balogh, J., Bollobás, B.: Bootstrap percolation on the hypercube. Probab. Theory Relat. Fields 134, 624–648 (2012)

    Article  MathSciNet  Google Scholar 

  10. Balogh, J., Bollobás, B., Duminil-Copin, H., Morris, R.: The sharp threshold for bootstrap percolation in all dimensions. Trans. Am. Math. Soc. 364(5), 2667–2701 (2012)

    Article  MathSciNet  Google Scholar 

  11. Balogh, J., Pittel, B.G.: Bootstrap percolation on the random regular graph. Random Struct. Algorithms 30(1–2), 257–286 (2007)

    Article  MathSciNet  Google Scholar 

  12. Bartal, A., Pliskin, N., Tsur, O.: Local/global contagion of viral/non-viral information: analysis of contagion spread in online social networks. PLoS ONE 15(4), e0230811 (2020)

    Article  Google Scholar 

  13. Bhansali, R., Schaposnik, L.P.: A trust model for spreading gossip in social networks: a multi-type bootstrap percolation model. Proc. Roy. Soc. A 476(2235), 20190826 (2020)

    Article  MathSciNet  Google Scholar 

  14. Bradonjić, M., Saniee, I.: Bootstrap percolation on random geometric graphs. Probab. Eng. Inf. Sci. 28(2), 169–181 (2014)

    Article  MathSciNet  Google Scholar 

  15. Candellero, E., Fountoulakis, N.: Bootstrap percolation and the geometry of complex networks. Stochast. Process. Appl. 126(1), 234–264 (2016)

    Article  MathSciNet  Google Scholar 

  16. Centola, D.: The spread of behavior in an online social network experiment. Science 329(5996), 1194–1197 (2010)

    Article  Google Scholar 

  17. Chalupa, J., Leath, P.L., Reich, G.R.: Bootstrap percolation on a Bethe lattice. J. Phys. C Solid State Phys. 12(1), L31–L35 (1979)

    Article  Google Scholar 

  18. Chung, F., Lu, L.: The diameter of sparse random graphs. Adv. Appl. Math. 26(4), 257–279 (2001)

    Article  MathSciNet  Google Scholar 

  19. Coja-Oghlan, A.: On the Laplacian eigenvalues of \(G_{n, p}\). Comb. Probab. Comput. 16(6), 923–946 (2007)

    Article  Google Scholar 

  20. Coja-Oghlan, A., Feige, U., Krivelevich, M., Reichman, D.: Contagious sets in expanders. In: 26th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2015), pp. 1953–1987. SIAM (2015)

    Google Scholar 

  21. Csardi, G., Nepusz, T.: The iGraph software package for complex network research. Int. J. Compl. Syst. 1695 (2006)

    Google Scholar 

  22. Doerr, B., Fouz, M., Friedrich, T.: Social networks spread rumors in sublogarithmic time. In: Proceedings of STOC, pp. 21–30 (2011)

    Google Scholar 

  23. Doerr, B., Fouz, M., Friedrich, T.: Why rumors spread so quickly in social networks. Commun. ACM 55(6), 70–75 (2012)

    Article  Google Scholar 

  24. Ebrahimi, R., Gao, J., Ghasemiesfeh, G., Schoenebeck, G.: Complex contagions in Kleinberg’s small world model. In: 6th Conference on Innovations in Theoretical Computer Science (ITCS 2015), pp. 63–72 (2015)

    Google Scholar 

  25. Friedman, J.: On the second eigenvalue and random walks in random \(d\)-regular graphs. Combinatorica 11, 331–362 (1991)

    Article  MathSciNet  Google Scholar 

  26. Gaffney, D.: #iranElection: Quantifying online activism. In: Proceedings of WebSci (2010)

    Google Scholar 

  27. Ghasemiesfeh, G., Ebrahimi, R., Gao, J.: Complex contagion and the weakness of long ties in social networks: revisited. In: 14th ACM Conference on Electronic Commerce (EC 2013), pp. 507–524 (2013)

    Google Scholar 

  28. González-Bailón, S., Borge-Holthoefer, J., Rivero, A., Moreno, Y.: The dynamics of protest recruitment through an online network. Sci. Rep. 1(197), 1–7 (2011)

    Google Scholar 

  29. Hoory, S., Linial, N., Wigderson, A.: Expander graphs and their applications. Bull. Amer. Math. Soc. (N.S.) 43(4), 439–561 (2006)

    Google Scholar 

  30. Jacquez, J.A., Simon, C.P., Koopman, J.: Structured mixing: heterogeneous mixing by the definition of activity groups. In: Castillo-Chavez, C. (ed.) Mathematical and Statistical Approaches to AIDS Epidemiology. LNB, vol. 83, pp. 301–315. Springer, Heidelberg (1989). https://doi.org/10.1007/978-3-642-93454-4_15

  31. Janson, S., łuczak, T., Turova, T., Vallier, T.: Bootstrap percolation on the random graph \(G_{n, p}\). Ann. Appl. Probabil. 22(5), 1989–2047 (2012)

    Google Scholar 

  32. Koch, C., Lengler, J.: Bootstrap percolation on geometric inhomogeneous random graphs. In: 43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016), pp. 147:1–147:15. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2016)

    Google Scholar 

  33. Krioukov, D., Papadopoulos, F., Kitsak, M., Vahdat, A., Boguñá, M.: Hyperbolic geometry of complex networks. Phys. Rev. E 82, 036106 (2010)

    Article  MathSciNet  Google Scholar 

  34. Krivelevich, M., Reichman, D., Samotij, W.: Smoothed analysis on connected graphs. SIAM J. Discret. Math. 29(3), 1654–1669 (2015)

    Article  MathSciNet  Google Scholar 

  35. Min, B., Miguel, M.S.: Competing contagion processes: complex contagion triggered by simple contagion. Sci. Rep. 8(1), 1–8 (2018)

    Google Scholar 

  36. Staudt, C.L., Sazonovs, A., Meyerhenke, H.: NetworKit: a tool suite for large-scale complex network analysis (2015)

    Google Scholar 

  37. Turova, T.S., Vallier, T.: Bootstrap percolation on a graph with random and local connections. J. Stat. Phys. 160(5), 1249–1276 (2015)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

We thank David Peleg for suggesting this research direction and for multiple discussions, and Noga Alon for suggesting the proof of Theorem 8. This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 945298-ParisRegionFP.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Philipp Fischbeck .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Cohen, S., Fischbeck, P., Friedrich, T., Krejca, M.S., Sauerwald, T. (2022). Accelerated Information Dissemination on Networks with Local and Global Edges. In: Parter, M. (eds) Structural Information and Communication Complexity. SIROCCO 2022. Lecture Notes in Computer Science, vol 13298. Springer, Cham. https://doi.org/10.1007/978-3-031-09993-9_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-09993-9_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-09992-2

  • Online ISBN: 978-3-031-09993-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics