International Symposium on Distributed Computing

Distributed Computing pp 480-496 | Cite as

Privacy-Conscious Information Diffusion in Social Networks

  • George Giakkoupis
  • Rachid Guerraoui
  • Arnaud Jégou
  • Anne-Marie Kermarrec
  • Nupur Mittal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9363)

Abstract

We present Riposte, a distributed algorithm for disseminating information (ideas, news, opinions, or trends) in a social network. Riposte ensures that information spreads widely if and only if a large fraction of users find it interesting, and this is done in a “privacy-conscious” manner, namely without revealing the opinion of any individual user. Whenever an information item is received by a user, Riposte decides to either forward the item to all the user’s neighbors, or not to forward it to anyone. The decision is randomized and is based on the user’s (private) opinion on the item, as well as on an upper bound s on the number of user’s neighbors that have not received the item yet. In short, if the user likes the item, Riposte forwards it with probability slightly larger than 1 / s, and if not, the item is forwarded with probability slightly smaller than 1 / s. Using a comparison to branching processes, we show for a general family of random directed graphs with arbitrary out-degree sequences, that if the information item appeals to a sufficiently large (constant) fraction of users, then the item spreads to a constant fraction of the network; while if fewer users like it, the dissemination process dies out quickly. In addition, we provide extensive experimental evaluation of Riposte on topologies taken from online social networks, including Twitter and Facebook.

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References

  1. 1.
    Alves, P., Ferreira, P.: AnonyLikes: anonymous quantitative feedback on social networks. In: Eyers, D., Schwan, K. (eds.) Middleware 2013. LNCS, vol. 8275, pp. 466–484. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  2. 2.
    Ambainis, A., Jakobsson, M., Lipmaa, H.: Cryptographic randomized response techniques. In: 7th International Workshop on Theory and Practice in Public Key Cryptography (PKC), pp. 425–438 (2004)Google Scholar
  3. 3.
    Athreya, K.B., Ney, P.E.: Branching processes. Springer (1972)Google Scholar
  4. 4.
    Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group formation in large social networks: Membership, growth, and evolution. In: 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 44–54 (2006)Google Scholar
  5. 5.
    Chaudhuri, A.: Randomized response and indirect questioning techniques in surveys. CRC Press (2010)Google Scholar
  6. 6.
    Chen, N., Olvera-Cravioto, M.: Directed random graphs with given degree distributions. Stochastic Systems 3(1), 147–186 (2013)MATHMathSciNetCrossRefGoogle Scholar
  7. 7.
    Ding, C., Chen, Y., Fu, X.: Crowd crawling: Towards collaborative data collection for large-scale online social networks. In: 1st ACM Conference on Online Social Networks (COSN), pp. 183–188 (2013)Google Scholar
  8. 8.
    Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: Halevi, S., Rabin, T. (eds.) TCC 2006. LNCS, vol. 3876, pp. 265–284. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  9. 9.
    Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Foundations and Trends in Theoretical Computer Science 9(3–4), 211–407 (2014)MathSciNetGoogle Scholar
  10. 10.
    Earl, J.: The dynamics of protest-related diffusion on the web. Information, Communication & Society 13(2), 209–225 (2010)CrossRefGoogle Scholar
  11. 11.
    Erlingsson, Ú., Pihur, V., Korolova, A.: RAPPOR: Randomized aggregatable privacy-preserving ordinal response. In: ACM Conference on Computer and Communications Security (CCS), pp. 1054–1067 (2014)Google Scholar
  12. 12.
    Garrett, K.: Protest in an information society: A review of literature on social movements and new icts. Information, Communication & Society 9(02), 202–224 (2006)CrossRefGoogle Scholar
  13. 13.
    Giakkoupis, G., Guerraoui, R., Jégou, A., Kermarrec, A.-M., Mittal, N.: Privacy-conscious information diffusion in social networks. Technical report, INRIA Rennes - Bretagne Atlantique, August 2015. https://hal.archives-ouvertes.fr/hal-01184246
  14. 14.
    Grasz, J.: Forty-five percent of employers use social networking sites to research job candidates, CareerBuilder survey finds. CareerBuilder Press Releases, August 2009. http://www.careerbuilder.com/share/aboutus/pressreleasesdetail.aspx?id=pr519&sd=8%2f19%2f2009&ed=12%2f31%2f2009&siteid=cbpr&sc_cmp1=cb_pr519_
  15. 15.
    Gupta, A., Hardt, M., Roth, A., Ullman, J.: Privately releasing conjunctions and the statistical query barrier. SIAM Journal on Computing 42(4), 1494–1520 (2013)MATHMathSciNetCrossRefGoogle Scholar
  16. 16.
    Haccou, P., Jagers, P., Vatutin, V.A.: Branching processes: Variation, growth, and extinction of populations. Cambridge Univ. Press (2005)Google Scholar
  17. 17.
    Kasiviswanathan, S.P., Lee, H.K., Nissim, K., Raskhodnikova, S., Smith, A.: What can we learn privately? SIAM Journal of Computing 40(3), 793–826 (2011)MATHMathSciNetCrossRefGoogle Scholar
  18. 18.
    Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: 19th International Conference on World Wide Web (WWW), pp. 591–600 (2010)Google Scholar
  19. 19.
    Leskovec, J., Lang, K.J., Dasgupta, A., Mahoney, M.W.: Community structure in large networks: Natural cluster sizes and the absence of large well-defined clusters. Internet Mathematics 6(1), 29–123 (2009)MATHMathSciNetCrossRefGoogle Scholar
  20. 20.
    Leskovec, J., Mcauley, J.J.: Learning to discover social circles in ego networks. In: Advances in Neural Information Processing Systems (NIPS), pp. 539–547 (2012)Google Scholar
  21. 21.
    Macskassy, S.A., Michelson, M.: Why do people retweet? Anti-homophily wins the day! In: 5th International Conference on Weblogs and Social Media (ICWSM) (2011)Google Scholar
  22. 22.
    McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: Homophily in social networks. Annual Review of Sociology 27, 415–444 (2001)CrossRefGoogle Scholar
  23. 23.
    Noelle-Neumann, E.: The spiral of silence a theory of public opinion. Journal of Communication 24(2), 43–51 (1974)CrossRefGoogle Scholar
  24. 24.
    NPR news In South Korea, old law leads to new crackdown, December 2011. http://www.npr.org/2011/12/01/142998183/in-south-korea-old-law-leads-to-new-crackdown
  25. 25.
    Quercia, D., Leontiadis, I., McNamara, L., Mascolo, C., Crowcroft, J.: SpotME if you can: Randomized responses for location obfuscation on mobile phones. In: 31st IEEE International Conference on Distributed Computing Systems (ICDCS), pp. 363–372 (2011)Google Scholar
  26. 26.
    TIME magazine. Indian women arrested over facebook post, November 2012. http://newsfeed.time.com/2012/11/19/indian-woman-arrested-over-facebook-like/
  27. 27.
    Warner, S.L.: Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association 60(309), 63–69 (1965)MATHCrossRefGoogle Scholar
  28. 28.
    Wilson, C., Boe, B., Sala, A., Puttaswamy, K.P., Zhao, B.Y.: User interactions in social networks and their implications. In: EuroSys, pp. 205–218 (2009)Google Scholar
  29. 29.
    Wulf, V., Misaki, K., Atam, M., Randall, D., Rohde, M.: ‘On the ground’ in Sidi Bouzid: Investigating social media use during the tunisian revolution. In: 16th ACM Conference on Computer Supported Cooperative Work (CSCW), pp. 1409–1418 (2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • George Giakkoupis
    • 1
  • Rachid Guerraoui
    • 2
  • Arnaud Jégou
    • 1
  • Anne-Marie Kermarrec
    • 1
  • Nupur Mittal
    • 1
  1. 1.INRIARennesFrance
  2. 2.EPFLLausanneSwitzerland

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