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User Analysis

LocaShare primarily focuses on giving users the ability to (i) select the type and amount of location information that they would like to share with others (for social or commercial purposes) and (ii) visualize the amount of information they have shared. The sharing of location data is important to anyone with a GPS in their phone. This is a broad population.

After doing some research \[1, 2, 3, 4\], we found that we can classify users based on their expertise in using software systems (to clear/update cookies in their browser, for example) and privacy concerns. Further categorization can be made depending on the type of data that users are interested in sharing (either for social or business purpose). With these classifications, we can divide users based on age in the following manner:

1. Wiki Markup
   <span style="color: #000000">teen

   teen

   -28:</span> less aware, amount actually shared (greatest in social network), least (commercial data), as danah boyd puts it “they lack the agency to assert social norms and expect that others will respect them” \[1\]. expertise (middle)

   1. Summary: less privacy concerns, medium expertise, most amount of social data, least amount of commercial/business data,
2. 28-60: more likely to share data with businesses, more proactive in refusing to share data, most expertise (in actively deleting cookies etc), more likely to have personal negative experiences
   1. Summary: medium privacy concerns, most expertise, medium amount of social data, most amount of commercial/business data,

3. Wiki Markup
   <span style="color: #000000">60+:</span> most conservative, have greatest privacy concerns, least amount of technical expertise,&nbsp; least likely to share data. Interestingly, \[1\] describes how none of their study participants expressed a need to create new acquaintances on the Web.

   1. Summary: most privacy concerns, least expertise, least amount of social data, medium amount of commercial/business data,

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of location data sharing services.

Example users in these categories are:

1. Joe, an unmarried college student who wants to update his friends about his visits to new or interesting places and is interested in receiving as many relevant offers as possible,
2. Bob, a married employee who cares a lot about the amount and type of information he shares with others, and wants to primarily connect with friends and family, and,
3. Carol, a middle-aged parent who primarily wants to keep track of her family members.

Less-savvy/non users:

This user is a middle-aged iPhone owner who does not currently use voluntary location sharing. She believes her location data is being used by a variety of applications, but isn’t sure which ones or what it’s used for.

...

The goal of this task is to review and perhaps change the type of data the user is sharing with others. The precondition is that one or more relationships have been previously established, and the desire to review or edit is generated either by curiosity, or by some recent behavior that a user might want to share or not share in some existing relationship. Because the user can see all of his/her own data here, the task may be performed multiple times per week. We expect people to be curious about their own data and how it appears to others. This activity can be learned by doing -- it just involves scrolling, clicking, zooming, and panning. Viewing is inherently very safe, and editing can be made more safe by including the option to undo actions. 

References:

\[1\] boyd, danah and Marwick, Alice E., Social Privacy in Networked Publics: Teens’ Attitudes, Practices, and Strategies (September 22, 2011). A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, September 2011. Available at SSRN: [http://ssrn.com/abstract=1925128

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\[2\] Hoofnagle, Chris Jay, King, Jennifer,  Li, Su and Turow, Joseph, How Different are Young Adults from Older  Adults When it Comes to Information Privacy Attitudes and Policies?  (April 14, 2010).  Available at SSRN: [http://ssrn.com/abstract=1589864

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] or [http://dx.doi.org/10.2139/ssrn.1589864

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\[3\] Vilma 

Lehtinen, Jaana Näsänen, and Risto Sarvas. 2009. "A little silly  and empty-headed": older adults' understandings of social networking  sites.  In _Proceedings of the 23rd British HCI Group Annual Conference on People and Computers: Celebrating People and Technology_ (BCS-HCI '09). British Computer Society, Swinton, UK, UK,  45-54.

\[4\] Johann Schrammel, Christina Köffel, and Manfred Tscheligi. 2009. How  much do you tell?: information disclosure behaviour indifferent types of  online communities.  In _Proceedings of the fourth international conference on Communities and technologies_ (C&T '09). ACM, New York, NY, USA,  275-284. DOI=10.1145/1556460.1556500 [http://doi.acm.org/10.1145/1556460.1556500

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TA Feedback.

This is a good start, but there are some big things missing. You don't actually discuss classes of users, just specific interviewees. Try to think about who your users are more holistically - right now they're sort of points along a 1D continuum.

You also don't seem to really get a good feel for what the tasks your users use to solve your problems, and instead you describe actions that your app will let users take. Don't forget that the next step is to make three separate designs - you shouldn't already have picked one. Think of task analysis as the analysis of tasks that need to be done to solve the problems.

Please also move your interview information to the GR1 page. I'd appreciate it if you made these changes, since we'll be working off this document for the whole rest of the project.\[1\]