Online trackers compile profiles on users for targeting ads, customizing websites, and selling users’ information. In this paper, we report on the first detailed study of the perceived benefits and risks of tracking-and the reasons behind them-conducted in the context of users’ own browsing histories. Prior work has studied this in the abstract; in contrast, we collected browsing histories from and interviewed 35 people about the perceived benefits and risks of online tracking in the context of their own browsing behavior. We find that many users want more control over tracking and think that controlled tracking has benefits, but are unwilling to put in the effort to control tracking or distrust current tools. We confirm previous findings that users’ general attitudes about tracking are often at odds with their comfort in specific situations. We also identify specific situational factors that contribute to users’ preferences about online tracking and explore how and why. Finally, we examine a sample of popular tools for controlling tracking and show that they only partially address the situational factors driving users’ preferences.We suggest opportunities to improve such tools, and explore the use of a classifier to automatically determine whether a user would be comfortable with tracking on a particular page visit; our results suggest this is a promising direction for future work.
 AAAA, ANA, BBB, DNA, and IAB. Self-regulatory principles for online behavioral advertising. Digital Advertising Alliance, July 2009.
 A. Acquisti. Privacy in electronic commerce and the economics of immediate gratification. In Proc. EC. ACM, 2004.
 L. Awarwal, N. Shrivastava, S. Jaiswa, and S. Panjwani. Do not embarrass: Re-examining user concerns for online tracking and advertising. In Proc. SOUPS, 2013.
 D. Bates, M. Maechler, B. M. Bolker, and S. Walker. lme4: Linear mixed-effects models using eigen and s4, 2014. ArXiv e-print; submitted to Journal of Statistical Software.
 R. F. Baumeister, E. Bratslavsky, C. Finkenauer, and K. D. Vohs. Bad is stronger than good. Review of general psychology, 5(4):323, 2001.
 H. Beales. The value of behavioral targeting. Network Advertising Initiative, 2010.
 B. Berendt, O. Günther, and S. Spiekermann. Privacy in e-commerce: stated preferences vs. actual behavior. Communications of the ACM, 48(4):101-106, 2005.
 M. Bilenko, M. Richardson, and J. Y. Tsai. Targeted, not tracked: Client-side solutions for privacy-friendly behavioral advertising. In HotPETs, 2011.
 I. A. Bureau. IAB internet advertising revenue report, Apr. 2015.
 R. Calo. Digital market manipulation. George Washington Law Review, 2013.
 F. Chanchary and S. Chiasson. User perceptions of sharing, advertising, and tracking. In Proc. SOUPS, 2015.
 C. Cortes and V. Vapnik. Support-vector networks. Machine Learning, 20(3), 1995.
 A. Datta, M. C. Tschantz, and A. Datta. Automated experiments on ad privacy settings. In Proc. PETS, 2015.
 A. Farahat and M. C. Bailey. How effective is targeted advertising? In Proc. WWW, 2012.
 M. Fredrikson and B. Livshits. Repriv: Re-imagining content personalization and in-browser privacy. In IEEE S&P, 2011.
 S. Greengard. Advertising gets personal. Communications of the ACM, 2012.
 S. Guha, A. Reznichenko, K. Tang, H. Haddadi, and P. Francis. Serving ads from localhost for performance, privacy, and profit. In HotNets, 2009.
 A. N. Joinson, U.-D. Reips, T. Buchanan, and C. B. P. Schofield. Privacy, trust, and self-disclosure online. Human- Computer Interaction, 25(1):1-24, 2010.
 A. Lambrecht and C. Tucker. When does retargeting work? Information specificity in online advertising. Journal of Marketing Research, 2013.
 P. Leon, B. Ur, R. Shay, Y. Wang, R. Balebako, and L. Cranor. Why Johnny can’t opt out: A usability evaluation of tools to limit online behavioral advertising. In Proc. CHI, 2012.
 P. G. Leon, B. Ur, Y. Wang, M. Sleeper, R. Balebako, R. Shay, L. Bauer, M. Christodorescu, and L. F. Cranor. What matters to users?: Factors that affect users’ willingness to share information with online advertisers. In Proc. SOUPS, 2013.
 M. Malheiros, S. Brostoff, C. Jennett, and M. A. Sasse. Would you sell your mother’s data? personal data disclosure in a simulated credit card application. In WEIS. 2012.
 M. Malheiros, S. Preibusch, and M. A. Sasse. "Fairly truthful": The impact of perceived effort, fairness, relevance, and sensitivity on personal data disclosure. In TRUST. 2013.
 K. Martin. Addressing privacy online-Initial analysis and draft findings. Unpublished research presentation, 2014.
 S. Panjwani, N. Shrivastava, S. Shukla, and S. Jaiswal. Understanding the privacy-personalization dilemma for web search: a user perspective. In Proc. CHI, 2013.
 K. Purcell, J. Brenner, and L. Rainie. Search engine use 2012. Technical report, 2012.
 E. J. Rader. Awareness of behavioral tracking and information privacy concern in Facebook and Google. In Proc. SOUPS, 2014.
 F. Roesner, T. Kohno, and D. Wetherall. Detecting and defending against third-party tracking on the web. In Proc. NSDI, 2012.
 F. Roesner, C. Rovillos, T. Kohno, and D. Wetherall. Balancing privacy and functionality of third-party social widgets. USENIX Magazine, 2012.
 V. Toubiana, A. Narayanan, D. Boneh, H. Nissenbaum, and S. Barocas. Adnostic: Privacy preserving targeted advertising. In Proc. NDSS, 2010.
 H. Treiblmaier and I. Pollach. Users’ perceptions of benefits and costs of personalization. In Proc. ICIS, 2007.
 C. Tucker. Social advertising. SSRN eLibrary, 2012. http: //ssrn.com/abstract=1975897.
 J. Turow. The daily you: How the new advertising industry is defining your identity and your worth. Yale University Press, 2012.
 J. Turow, J. King, C. J. Hoofnagle, A. Bleakley, and M. Hennessy. Americans reject tailored advertising and three activities that enable it. SSRN, 2009.
 B. Ur, P. G. Leon, L. F. Cranor, R. Shay, and Y. Wang. Smart, useful, scary, creepy: Perceptions of online behavioral advertising. In Proc. SOUPS, 2012.
 P. A. Viola and M. J. Jones. Fast and robust classification using Asymmetric AdaBoost and a detector cascade. In NIPS, 2001.
 C. E. Wills and M. Zeljkovic. A personalized approach to web privacy: Awareness, attitudes and actions. Information Management & Computer Security, 2011.
 C. Wilson. If you use a Mac or an Android, e-commerce sites may be charging you more, Nov. 2014. http://www.washingtonpost.com/posteverything/wp/2014/11/03/ifyou-use-a-mac-or-an-android-e-commerce-sites\-may-becharging-you-more/.
 D. A. A. with Zogby Analytics. Poll: Internet Users Recognize the Importance of Online Advertising and the Value of Self-Regulation. http://www.aboutads.info/ZogbyDAAOct13PollResults.pdf.