Users dealing with spam and spam filters: some observations and recommendations

ABSTRACT

The email communication system is threatened by unsolicited commercial email aka spam. In response, spam filters have been deployed widely to help reduce the amount of spam users have to cope with. This paper describes work towards helping users better understand the often complex decision making that is spam filtering. An investigation of a number of popular web-based email services suggests that the filtering process is typically implemented as a black box allowing very little user involvement. In order to explore how we could help users understand how spam filters work and how they assess messages we conducted a number of user experiments using a simulated email interface providing richer spam filtering information than the webmail interfaces we investigated. Feedback indicates that additional information provided by the interface would be welcome and suggests to further investigate ways to involve users in the filtering process.

REFERENCES

• 1: Christopher Ahlberg , Christopher Williamson , Ben Shneiderman, Dynamic queries for information exploration: an implementation and evaluation, Proceedings of the SIGCHI conference on Human factors in computing systems, p.619-626, May 03-07, 1992, Monterey, California, United States [doi>10.1145/142750.143054]
• 2: Jeff Balvanz , Don Paulsen , Joe Struss, Spam software evaluation, training, and support: fighting back to reclaim the email inbox, Proceedings of the 32nd annual ACM SIGUCCS conference on User services, p.385-387, October 10-13, 2004, Baltimore, MD, USA [doi>10.1145/1027802.1027897]
• 3: Cage, S. (2004). UN seeks spam mandate. The Australian 07/07/04. Article available at URL http://australianit.news.com.au/articles/0,7204,10066694%5E15306%5E%5Enbv%5E,00.html
• 4: CEAS Conference on Email and Anti-Spam 2004--2007. Proceedings (currently up to 2006) available at URL http://www.ceas.cc
• 5: Fallows, D. (2003). Spam. How it is hurting email and degrading life on the internet. Report published October 22, 2003 by the Pew Internet & American Life project. Washington, DC, USA.
• 6: Li, X. (2006). E-marketing, unsolicited commercial e-mail, and legal solutions. Webology, 3(1), Article 23. Retrieved October 20, 2006, from http://www.webology.ir/2006/v3nl/a23.html
• 7: Lueg, C., Huang, J. and Twidale, M. (2007). Mystery Meat revisited: Spam, Anti-Spam Measures and Digital Redlining. Webology 4(1) March (ISSN 1735--188X).
• 8: Lueg, C. (2005). From Spam Filtering to Information Retrieval and Back: Seeking Conceptual Foundations for Spam Filtering. Proceedings of the 69th Annual Conference of the American Society for Information Science and Technology, Charlotte NC, USA
• 9: Lueg, C. (2004). The Hidden Impacts of Anti-Spam Measures and their Contributions to the Digital Divide: An Exploratory Study. Proceedings of the 68th Annual Meeting of the American Society for Information Science and Technology, Providence RI, USA.
• 10: Martin, S. P. (2006). Informative Spam Interface. BComp (Hons) Thesis, University of Tasmania, Australia.
• 11: NOIE (2002). Final report of the Australian National Office for the Information Economy (NOIE) review of the spam problem and how it can be countered. Report available at http://www.noie.gov.au/projects/confidence/Improving/Spam/Interim_Report/contents.htm (accessed 03/05/2003).
• 12: Twidale, M. (2004). Worrying about infrastructures. Workshop "Distributed Collective Practice: Building new Directions for Infrastructural Studies" of the 2004 ACM Conference on Computer Supported Cooperative Work, Nov 2004, Chicago.
• 13: Brian Whitworth , Elizabeth Whitworth, Spam and the Social-Technical Gap, Computer, v.37 n.10, p.38-45, October 2004 [doi>10.1109/MC.2004.177]
• 14: Wright, C. (2003). Can't get spam when you need it. The Age November.
• 15: Shoshana Zuboff, In the age of the smart machine: the future of work and power, Basic Books, Inc., New York, NY, 1988

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.m Miscellaneous

Keywords:
electronic mail, information retrieval, information search, informative interfaces, spam