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Toward Automatic Censorship Detection in Microblogs

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Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8643))

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Abstract

Social media is an area where users often experience censorship through a variety of means such as the restriction of search terms or active and retroactive deletion of messages. In this paper we examine the feasibility of automatically detecting censorship of microblogs. We use a network growing model to simulate discussion over a microblog follow network and compare two censorship strategies to simulate varying levels of message deletion. Using topological features extracted from the resulting graphs, a classifier is trained to detect whether or not a given communication graph has been censored. The results show that censorship detection is feasible under empirically measured levels of message deletion. The proposed framework can enable automated censorship measurement and tracking, which, when combined with aggregated citizen reports of censorship, can allow users to make informed decisions about online communication habits.

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Notes

  1. 1.

    If actors A and B are connected and B and C are connected, there is a high probability that actors A and C are also connected.

  2. 2.

    Diameter and radius are calculated on the largest connected component.

  3. 3.

    http://www.cs.waikato.ac.nz/ml/weka/

  4. 4.

    We omit plots for the Laplacian eigenvalues due to space considerations.

References

  1. Bamman, D., O’Connor, B., Smith, N.A.: Censorship and deletion practices in Chinese social media. First Monday 17(3) (2012)

    Google Scholar 

  2. Chakrabarti, D.: Graph mining: laws, generators, and algorithms. ACM Comput. Surv. (CSUR) 38 (2006). http://dl.acm.org/citation.cfm?id=1132954

  3. Clauset, A., Shalizi, C.R., Newman, M.E.J.: Power-law distributions in empirical data. SIAM Rev. 51(4), 661–703 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  4. Cohen, R., Erez, K., Ben-Avraham, D., Havlin, S.: Breakdown of the internet under intentional attack. Phys. Rev. Lett. 86(16), 3682–3685 (2001)

    Article  Google Scholar 

  5. Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273–297 (1995)

    MATH  Google Scholar 

  6. Costenbader, E., Valente, T.W.: The stability of centrality measures when networks are sampled. Soc. Netw. 25(4), 283–307 (2003)

    Article  Google Scholar 

  7. Crandall, J.R., Zinn, D., Byrd, M., Barr, E.T., East, R.: ConceptDoppler: a weather tracker for internet censorship. In: ACM Conference on Computer and Communications Security, pp. 352–365 (2007)

    Google Scholar 

  8. Deibert, R.: Black code redux: censorship, surveillance, and the militarization of cyberspace. In: Boler, M. (ed.) Digital Media and Democracy: Tactics in Hard Times, pp. 137–164. MIT Press, Cambridge (2008)

    Google Scholar 

  9. Dick, A., Oyieke, L., Bothma, T.: Are established democracies less vulnerable to Internet censorship than authoritarian regimes?: The social media test. Technical report, Committee on Freedom of Access to Information and Freedom of Expression (FAIFE), University of Pretoria, South Africa (2012)

    Google Scholar 

  10. Fang, Z., Wang, J., Liu, B., Gong, W.: Double pareto lognormal distributions in complex networks. In: Thai, M.T., Pardalos, P.M. (eds.) Handbook of Optimization in Complex Networks, pp. 55–80. Springer, New York (2012)

    Chapter  Google Scholar 

  11. Gallos, L.K., Argyrakis, P., Bunde, A., Cohen, R., Havlin, S.: Tolerance of scale-free networks: from friendly to intentional attack strategies. Phys. A: Stat. Mech. Appl. 344(3), 504–509 (2004)

    Article  Google Scholar 

  12. Hwang, T.: Herdict: a distributed model for threats online. Netw. Secur. 2007(8), 15–18 (2007). http://www.sciencedirect.com/science/article/pii/S1353485807700740

    Article  Google Scholar 

  13. Kempe, D., Kleinberg, J., Tardos, E.: Maximizing the spread of influence through a social network, p. 137 (2003)

    Google Scholar 

  14. Leskovec, J., Kleinberg, J.M., Faloutsos, C.: Graph evolution: densification and shrinking diameters. TKDD 1(1), 1–40 (2007)

    Article  Google Scholar 

  15. MacKinnon, R.: Consent of the Networked: The Worldwide Struggle For Internet Freedom. Basic Books, New York (2012)

    Google Scholar 

  16. Morrison, D., Mcloughlin, I., Hogan, A., Hayes, C.: Evolutionary clustering and analysis of user behaviour in online forums. In: Proceedings of ICWSM-12, 6th International AAAI Conference on Weblogs and Social Media (2012)

    Google Scholar 

  17. Newman, M.E., Strogatz, S.H., Watts, D.J.: Random graphs with arbitrary degree distributions and their applications. Phys. Rev. E 64(2), 026118 (2001)

    Article  Google Scholar 

  18. Nuss, J.: Web site tracks world online censorship reports, 4 August 2009. http://phys.org/news168613309.html

  19. Roberts, H., Zuckerman, E., Palfrey, J.: Circumvention tool evaluation. Technical report (2011)

    Google Scholar 

  20. Sang-Hun, C.: Korea Policing the Net. Twist? Its South Korea, 12 August 2012. http://www.nytimes.com/2012/08/13/world/asia/critics-see-south-korea-internet-curbs-as-censorship.html

  21. Stone, B.: The Inexact Science Behind D.M.C.A. Takedown Notices, 5 June 2008. http://bits.blogs.nytimes.com/2008/06/05/the-inexact-science-behind-dmca-takedown-notices/

  22. Takahashi, D.Y., Sato, J.R., Ferreira, C.E., Fujita, A.: Discriminating different classes of biological networks by analyzing the graphs spectra distribution. CoRR abs/1208.2976 (2012)

    Google Scholar 

  23. Yadav, G., Babu, S.: NEXCADE: perturbation analysis for complex networks. PloS One 7(8), e41827 (2012)

    Article  Google Scholar 

  24. Zhu, T., Phipps, D., Pridgen, A., Crandall, J.R., Wallach, D.S.: Tracking and quantifying censorship on a chinese microblogging site. CoRR abs/1211.6166 (2012)

    Google Scholar 

  25. Zhu, T., Phipps, D., Pridgen, A., Crandall, J.R., Wallach, D.S.: The velocity of censorship: High-fidelity detection of microblog post deletions. CoRR abs/1303.0597 (2013)

    Google Scholar 

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Acknowledgments

This work was funded by the European Union (EU) and Science Foundation Ireland (SFI) in the course of the projects ROBUST (EU grant no. 257859) and CLIQUE Strategic Research Cluster (SFI grant no. 08/SRC/I1407), and LION-2 (SFI grant no. SFI/08/CE/I1380).

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Authors and Affiliations

  1. Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway

    Donn Morrison

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  1. Donn Morrison
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Correspondence to Donn Morrison .

Editor information

Editors and Affiliations

  1. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Chih Peng

  2. Google Research, Mountain View, California, USA

    Haixun Wang

  3. University of Melbourne, Melbourne, Victoria, Australia

    James Bailey

  4. National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  5. Japan Advanced Institute of Science and Technology, Nomi City, Japan

    Tu Bao Ho

  6. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  7. National Chengchi University, Taipei, Taiwan

    Arbee L.P. Chen

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Morrison, D. (2014). Toward Automatic Censorship Detection in Microblogs. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_51

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  • DOI: https://doi.org/10.1007/978-3-319-13186-3_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13185-6

  • Online ISBN: 978-3-319-13186-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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