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Using Uncensored Communication Channels to Divert Spam Traffic

Author

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  • Benjamin Chiao

    (University of Michigan, Ann Arbor)

  • Jeffrey MacKie-Mason

    (University of Michigan, Ann Arbor)

Abstract

We offer a microeconomic model of the two-sided market for the dominant form of spam: bulk, unsolicited, and commercial advertising email. We adopt an incentive-centered design approach to develop a simple, feasible improvement to the current email system using an uncensored communication channel. Such a channel could be an email folder or account, to which properly tagged commercial solicitations are routed. We characterize the circumstances under which spammers would voluntarily move much of their spam into the open channel, leaving the traditional email channel dominated by person-to-person, non-spam mail. Our method follows from observing that there is a real demand for unsolicited commercial email, so that everyone can be made better off if a channel is provided for spammers to meet spamdemanders. As a bonus, the absence of filtering in an open channel restores to advertisers the incentive to make messages truthful, rather than to disguise them to avoid filters. We show that under certain conditions all email recipients are better off when an open channel is introduced. Only recipients wanting spam will use the open channel enjoying the less disguised messages, and for all recipients the satisfaction associated with desirable mail received increases, and dissatisfaction associated with both undesirable mail received and desirable mail filtered out decreases.

Suggested Citation

  • Benjamin Chiao & Jeffrey MacKie-Mason, 2006. "Using Uncensored Communication Channels to Divert Spam Traffic," Working Papers 06-20, NET Institute, revised Oct 2006.
  • Handle: RePEc:net:wpaper:0620
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    References listed on IDEAS

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    1. Il-Horn Hann & Kai-Lung Hui & Sang-Yong Tom Lee & Ivan Png, 2005. "Consumer Privacy and Marketing Avoidance," Industrial Organization 0503009, University Library of Munich, Germany.
    2. Geoffrey G. Parker & Marshall W. Van Alstyne, 2005. "Two-Sided Network Effects: A Theory of Information Product Design," Management Science, INFORMS, vol. 51(10), pages 1494-1504, October.
    3. Il-Horn Hann & Kai-Lung Hui & Yee-Lin Lai & S.Y.T. Lee & I.P.L. PNG, 2006. "Who gets spammed?," Natural Field Experiments 00271, The Field Experiments Website.
    4. Simon P. Anderson & André de Palma, 2012. "Competition for attention in the Information (overload) Age," RAND Journal of Economics, RAND Corporation, vol. 43(1), pages 1-25, March.
    5. Loder Theodore & Van Alstyne Marshall & Wash Rick, 2006. "An Economic Response to Unsolicited Communication," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 6(1), pages 1-38, March.
    6. Jean-Charles Rochet & Jean Tirole, 2003. "Platform Competition in Two-Sided Markets," Journal of the European Economic Association, MIT Press, vol. 1(4), pages 990-1029, June.
    7. Simon P. Anderson & André De Palma, 2009. "Information congestion," RAND Journal of Economics, RAND Corporation, vol. 40(4), pages 688-709, December.
    8. Timothy Van Zandt, 2004. "Information Overload in a Network of Targeted Communication," RAND Journal of Economics, The RAND Corporation, vol. 35(3), pages 542-560, Autumn.
    9. Robert Kraut & Shyam Sunder & Rahul Telang & James Morris, 2005. "Pricing Electronic Mail to Solve the Problem of Spam," Yale School of Management Working Papers amz2638, Yale School of Management, revised 01 Oct 2005.
    10. Il-Horn Hann & Kai-Lung Hui & Sang-Yong T. Lee & Ivan P. L. Png, 2008. "Consumer Privacy and Marketing Avoidance: A Static Model," Management Science, INFORMS, vol. 54(6), pages 1094-1103, June.
    11. Bagwell, Kyle, 2007. "The Economic Analysis of Advertising," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 28, pages 1701-1844, Elsevier.
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    More about this item

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications

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